Package: a4 Version: 1.8.0 Depends: a4Base, a4Preproc, a4Classif, a4Core, a4Reporting Suggests: MLP, nlcv, ALL, Cairo License: GPL-3 MD5sum: 1186447fdffea37e65539f93f3bc9465 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Umbrella Package Description: Automated Affymetrix Array Analysis Umbrella Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/a4_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/a4_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/a4_1.8.0.tgz vignettes: vignettes/a4/inst/doc/a4vignette.pdf vignetteTitles: a4vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/a4/inst/doc/a4vignette.R Package: a4Base Version: 1.8.0 Depends: methods, graphics, grid, Biobase, AnnotationDbi, annaffy, mpm, genefilter, limma, multtest, glmnet, a4Preproc, a4Core, gplots Suggests: Cairo, ALL Enhances: gridSVG, JavaGD License: GPL-3 MD5sum: 22bd9c761f21fba19634cdd5dca9cc81 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Base Package Description: Automated Affymetrix Array Analysis biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke, Tine Casneuf, An De Bondt, Steven Osselaer and Hinrich Goehlmann Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Base_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/a4Base_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/a4Base_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/a4Base_1.8.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: a4Classif Version: 1.8.0 Depends: methods, a4Core, a4Preproc, MLInterfaces, ROCR, pamr, glmnet, varSelRF Imports: a4Core Suggests: ALL License: GPL-3 MD5sum: 69fd31ccdbcb00426eba17d6768ba2a0 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Classification Package Description: Automated Affymetrix Array Analysis Classification Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Classif_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/a4Classif_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/a4Classif_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/a4Classif_1.8.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: a4Core Version: 1.8.0 Depends: methods, Biobase, glmnet License: GPL-3 MD5sum: e8a114696e972577d36f099856a25dd8 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Core Package Description: Automated Affymetrix Array Analysis Core Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Core_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/a4Core_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/a4Core_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/a4Core_1.8.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4, a4Base, a4Classif importsMe: a4Classif Package: a4Preproc Version: 1.8.0 Depends: methods, AnnotationDbi Suggests: ALL, hgu95av2.db License: GPL-3 MD5sum: 20b37bf48830873c5f23c1622f3a2c50 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Preprocessing Package Description: Automated Affymetrix Array Analysis Preprocessing Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Preproc_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/a4Preproc_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/a4Preproc_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/a4Preproc_1.8.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4, a4Base, a4Classif Package: a4Reporting Version: 1.8.0 Depends: methods, annaffy Imports: xtable, utils License: GPL-3 MD5sum: 2a8c4ce10914f7ed3c6aad0eaf73e879 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Reporting Package Description: Automated Affymetrix Array Analysis Reporting Package biocViews: Microarray Author: Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Reporting_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/a4Reporting_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/a4Reporting_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/a4Reporting_1.8.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: ABarray Version: 1.28.0 Imports: Biobase, graphics, grDevices, methods, multtest, stats, tcltk, utils Suggests: limma, LPE License: GPL MD5sum: 00e05294b98290af0256cf1298cd5d79 NeedsCompilation: no Title: Microarray QA and statistical data analysis for Applied Biosystems Genome Survey Microrarray (AB1700) gene expression data. Description: Automated pipline to perform gene expression analysis for Applied Biosystems Genome Survey Microarray (AB1700) data format. Functions include data preprocessing, filtering, control probe analysis, statistical analysis in one single function. A GUI interface is also provided. The raw data, processed data, graphics output and statistical results are organized into folders according to the analysis settings used. biocViews: Microarray, OneChannel, Preprocessing Author: Yongming Andrew Sun Maintainer: Yongming Andrew Sun source.ver: src/contrib/ABarray_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ABarray_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ABarray_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ABarray_1.28.0.tgz vignettes: vignettes/ABarray/inst/doc/ABarrayGUI.pdf, vignettes/ABarray/inst/doc/ABarray.pdf vignetteTitles: ABarray gene expression GUI interface, ABarray gene expression hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ABarray/inst/doc/ABarrayGUI.R, vignettes/ABarray/inst/doc/ABarray.R Package: aCGH Version: 1.38.0 Depends: R (>= 2.10), cluster, survival, multtest Imports: Biobase, cluster, grDevices, graphics, methods, multtest, stats, survival, splines, utils License: GPL-2 Archs: i386, x64 MD5sum: 117cb93be5068e1810e44cce22fbf716 NeedsCompilation: yes Title: Classes and functions for Array Comparative Genomic Hybridization data. Description: Functions for reading aCGH data from image analysis output files and clone information files, creation of aCGH S3 objects for storing these data. Basic methods for accessing/replacing, subsetting, printing and plotting aCGH objects. biocViews: CopyNumberVariants, DataImport, Genetics Author: Jane Fridlyand , Peter Dimitrov Maintainer: Peter Dimitrov source.ver: src/contrib/aCGH_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/aCGH_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/aCGH_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/aCGH_1.38.0.tgz vignettes: vignettes/aCGH/inst/doc/aCGH.pdf vignetteTitles: aCGH Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/aCGH/inst/doc/aCGH.R dependsOnMe: ADaCGH2, CRImage importsMe: snapCGH suggestsMe: beadarraySNP Package: ACME Version: 2.16.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), methods Imports: graphics, stats License: GPL (>= 2) Archs: i386, x64 MD5sum: 87f875218622a89fbf8073da38e9dd06 NeedsCompilation: yes Title: Algorithms for Calculating Microarray Enrichment (ACME) Description: ACME (Algorithms for Calculating Microarray Enrichment) is a set of tools for analysing tiling array ChIP/chip, DNAse hypersensitivity, or other experiments that result in regions of the genome showing "enrichment". It does not rely on a specific array technology (although the array should be a "tiling" array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory. biocViews: Bioinformatics Author: Sean Davis Maintainer: Sean Davis URL: http://watson.nci.nih.gov/~sdavis source.ver: src/contrib/ACME_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ACME_2.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ACME_2.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ACME_2.16.0.tgz vignettes: vignettes/ACME/inst/doc/ACME.pdf vignetteTitles: ACME hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ACME/inst/doc/ACME.R Package: ADaCGH2 Version: 1.10.0 Depends: R (>= 2.11.0), tilingArray, aCGH, waveslim, cluster, snapCGH, snowfall, ff Suggests: GLAD, DNAcopy, CGHregions, rlecuyer Enhances: Rmpi, multicore License: GPL (>= 3) Archs: i386, x64 MD5sum: 4a67a7364e9735a9dc4f397888dcadcf NeedsCompilation: yes Title: Analysis of data from aCGH experiments using parallel computing and ff objects Description: Analysis and plotting of array CGH data. Allows usage of Circular Binary Segementation, wavelet-based smoothing (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), HMM, BioHMM, GLAD, CGHseg. Most computations are parallelized. biocViews: Microarray, CopyNumberVariants Author: Ramon Diaz-Uriarte , Oscar M. Rueda . Wavelet-based aCGH smoothing code from Li Hsu and Douglas Grove . Imagemap code from Barry Rowlingson . HaarSeg code from Erez Ben-Yaacov; downloaded from Maintainer: Ramon Diaz-Uriarte URL: http://launchpad.net/adacgh, http://wavicgh.bioinfo.cnio.es source.ver: src/contrib/ADaCGH2_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ADaCGH2_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ADaCGH2_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ADaCGH2_1.10.0.tgz vignettes: vignettes/ADaCGH2/inst/doc/ADaCGH2.pdf vignetteTitles: ADaCGH2 Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ADaCGH2/inst/doc/ADaCGH2.R Package: adSplit Version: 1.30.0 Depends: R (>= 2.1.0), methods (>= 2.1.0) Imports: AnnotationDbi, Biobase (>= 1.5.12), cluster (>= 1.9.1), GO.db (>= 1.8.1), graphics, grDevices, KEGG.db (>= 1.8.1), methods, multtest (>= 1.6.0), stats (>= 2.1.0) Suggests: golubEsets (>= 1.0), vsn (>= 1.5.0), hu6800.db (>= 1.8.1) License: GPL (>= 2) Archs: i386, x64 MD5sum: 8714925dfea622b1cc62cb496424f7cf NeedsCompilation: yes Title: Annotation-Driven Clustering Description: This package implements clustering of microarray gene expression profiles according to functional annotations. For each term genes are annotated to, splits into two subclasses are computed and a significance of the supporting gene set is determined. biocViews: Microarray, Bioinformatics, Clustering Author: Claudio Lottaz, Joern Toedling Maintainer: Claudio Lottaz URL: http://compdiag.molgen.mpg.de/software/index.shtml source.ver: src/contrib/adSplit_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/adSplit_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/adSplit_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/adSplit_1.30.0.tgz vignettes: vignettes/adSplit/inst/doc/bcb_logo.pdf, vignettes/adSplit/inst/doc/minerva_bcb.pdf, vignettes/adSplit/inst/doc/tr_2005_02.pdf vignetteTitles: bcb_logo.pdf, minerva_bcb.pdf, Annotation-Driven Clustering hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/adSplit/inst/doc/tr_2005_02.R Package: affxparser Version: 1.32.3 Depends: R (>= 2.6.0) Suggests: R.utils (>= 1.19.5), AffymetrixDataTestFiles License: LGPL (>= 2) Archs: i386, x64 MD5sum: c42039635febc494ae748aebd53af31f NeedsCompilation: yes Title: Affymetrix File Parsing SDK Description: Package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It provides methods for fast and memory efficient parsing of Affymetrix files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based files are supported. Currently, there are methods for reading chip definition file (CDF) and a cell intensity file (CEL). These files can be read either in full or in part. For example, probe signals from a few probesets can be extracted very quickly from a set of CEL files into a convenient list structure. biocViews: Infrastructure, DataImport Author: Henrik Bengtsson, James Bullard, Robert Gentleman, Kasper Daniel Hansen, Martin Morgan Maintainer: Kasper Daniel Hansen source.ver: src/contrib/affxparser_1.32.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/affxparser_1.32.3.zip win64.binary.ver: bin/windows64/contrib/2.16/affxparser_1.32.3.zip mac.binary.ver: bin/macosx/contrib/2.16/affxparser_1.32.3.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: ITALICS, pdInfoBuilder, rMAT, Starr importsMe: affyILM, AffyTiling, cn.farms, GeneRegionScan, ITALICS, oligo, rMAT Package: affy Version: 1.38.1 Depends: R (>= 2.8.0), BiocGenerics (>= 0.1.12), Biobase (>= 2.5.5) Imports: BiocGenerics, Biobase, affyio (>= 1.13.3), BiocInstaller, graphics, grDevices, methods, preprocessCore, stats, utils, zlibbioc LinkingTo: preprocessCore Suggests: tkWidgets (>= 1.19.0), affydata, widgetTools License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: c5d15f118df86b892fd5b55792a99cb9 NeedsCompilation: yes Title: Methods for Affymetrix Oligonucleotide Arrays Description: The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it. biocViews: Microarray, OneChannel, Preprocessing Author: Rafael A. Irizarry , Laurent Gautier , Benjamin Milo Bolstad , and Crispin Miller with contributions from Magnus Astrand , Leslie M. Cope , Robert Gentleman, Jeff Gentry, Conrad Halling , Wolfgang Huber, James MacDonald , Benjamin I. P. Rubinstein, Christopher Workman , John Zhang Maintainer: Rafael A. Irizarry source.ver: src/contrib/affy_1.38.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/affy_1.38.1.zip win64.binary.ver: bin/windows64/contrib/2.16/affy_1.38.1.zip mac.binary.ver: bin/macosx/contrib/2.16/affy_1.38.1.tgz vignettes: vignettes/affy/inst/doc/affy.pdf, vignettes/affy/inst/doc/builtinMethods.pdf, vignettes/affy/inst/doc/customMethods.pdf, vignettes/affy/inst/doc/vim.pdf vignetteTitles: 1. Primer, 2. Built-in Processing Methods, 3. Custom Processing Methods, 4. Import Methods hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affy/inst/doc/affy.R, vignettes/affy/inst/doc/builtinMethods.R, vignettes/affy/inst/doc/customMethods.R, vignettes/affy/inst/doc/vim.R dependsOnMe: affyContam, affycoretools, AffyExpress, affylmGUI, affyPara, affypdnn, affyPLM, affyQCReport, AffyRNADegradation, altcdfenvs, arrayMvout, ArrayTools, bgx, Cormotif, DrugVsDisease, dualKS, ExiMiR, farms, frmaTools, gcrma, LMGene, logitT, maDB, maskBAD, MLP, panp, plw, prebs, puma, qpcrNorm, ReadqPCR, RefPlus, rHVDM, Risa, RPA, simpleaffy, sscore, Starr, webbioc importsMe: affyILM, affyQCReport, AffyTiling, ArrayExpress, arrayQualityMetrics, ArrayTools, ChIPXpress, Cormotif, farms, ffpe, frma, gcrma, GEOsubmission, Harshlight, HTqPCR, lumi, makecdfenv, MSnbase, plier, plw, puma, pvac, simpleaffy, tilingArray, TurboNorm, virtualArray, vsn, waveTiling suggestsMe: AnnotationForge, beadarray, beadarraySNP, BiocCaseStudies, Biostrings, BufferedMatrixMethods, categoryCompare, ecolitk, ExpressionView, factDesign, ffpe, gCMAPWeb, GeneRegionScan, limma, made4, oneChannelGUI, piano, PREDA, siggenes, TurboNorm Package: affycomp Version: 1.36.0 Depends: R (>= 2.13.0), methods, Biobase (>= 2.3.3) Suggests: splines, affycompData License: GPL (>= 2) MD5sum: 00f296105fec4875ff163f8aefa9c53b NeedsCompilation: no Title: Graphics Toolbox for Assessment of Affymetrix Expression Measures Description: The package contains functions that can be used to compare expression measures for Affymetrix Oligonucleotide Arrays. biocViews: OneChannel, Microarray, Preprocessing Author: Rafael A. Irizarry and Zhijin Wu with contributions from Simon Cawley Maintainer: Rafael A. Irizarry source.ver: src/contrib/affycomp_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affycomp_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affycomp_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affycomp_1.36.0.tgz vignettes: vignettes/affycomp/inst/doc/affycomp.pdf vignetteTitles: affycomp primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affycomp/inst/doc/affycomp.R Package: AffyCompatible Version: 1.20.0 Depends: R (>= 2.7.0), XML (>= 2.8-1), RCurl (>= 0.8-1), methods Imports: Biostrings License: Artistic-2.0 MD5sum: 6e0fa763ba664b8b240c4925a2e20833 NeedsCompilation: no Title: Affymetrix GeneChip software compatibility Description: This package provides an interface to Affymetrix chip annotation and sample attribute files. The package allows an easy way for users to download and manage local data bases of Affynmetrix NetAffx annotation files. The package also provides access to GeneChip Operating System (GCOS) and GeneChip Command Console (AGCC)-compatible sample annotation files. biocViews: Infrastructure, Microarray, OneChannel Author: Martin Morgan, Robert Gentleman Maintainer: Martin Morgan source.ver: src/contrib/AffyCompatible_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AffyCompatible_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AffyCompatible_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AffyCompatible_1.20.0.tgz vignettes: vignettes/AffyCompatible/inst/doc/MAGEAndARR.pdf, vignettes/AffyCompatible/inst/doc/NetAffxResource.pdf vignetteTitles: Retrieving MAGE and ARR sample attributes, Annotation retrieval with NetAffxResource hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyCompatible/inst/doc/MAGEAndARR.R, vignettes/AffyCompatible/inst/doc/NetAffxResource.R importsMe: IdMappingRetrieval Package: affyContam Version: 1.18.0 Depends: R (>= 2.7.0), tools, methods, utils, Biobase, affy, affydata License: Artistic-2.0 MD5sum: 3c00b08b2304f89d8a6f0f15107b8699 NeedsCompilation: no Title: structured corruption of affymetrix cel file data Description: structured corruption of cel file data to demonstrate QA effectiveness biocViews: Infrastructure, Bioinformatics Author: V. Carey Maintainer: V. Carey source.ver: src/contrib/affyContam_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affyContam_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affyContam_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affyContam_1.18.0.tgz vignettes: vignettes/affyContam/inst/doc/affyContam.pdf vignetteTitles: affy contamination tools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyContam/inst/doc/affyContam.R Package: affycoretools Version: 1.32.1 Depends: affy, Biobase, GO.db, KEGG.db Imports: biomaRt, limma, GOstats, annotate, annaffy, genefilter, gcrma, splines, xtable, AnnotationDbi, lattice, gplots, R2HTML, oligoClasses, ReportingTools, hwriter Suggests: affydata, hgfocuscdf, rgl License: Artistic-2.0 MD5sum: d9547cabb56b4a5b1f38273f873442d0 NeedsCompilation: no Title: Functions useful for those doing repetitive analyses with Affymetrix GeneChips. Description: Various wrapper functions that have been written to streamline the more common analyses that a core Biostatistician might see. biocViews: ReportWriting, Microarray, OneChannel, GeneExpression Author: James W. MacDonald Maintainer: James W. MacDonald source.ver: src/contrib/affycoretools_1.32.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/affycoretools_1.32.1.zip win64.binary.ver: bin/windows64/contrib/2.16/affycoretools_1.32.1.zip mac.binary.ver: bin/macosx/contrib/2.16/affycoretools_1.32.1.tgz vignettes: vignettes/affycoretools/inst/doc/affycoretools_biomaRt.pdf, vignettes/affycoretools/inst/doc/affycoretools.pdf vignetteTitles: affycoretools biomaRt Integration, affycoretools Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affycoretools/inst/doc/affycoretools_biomaRt.R, vignettes/affycoretools/inst/doc/affycoretools.R suggestsMe: Agi4x44PreProcess Package: AffyExpress Version: 1.26.0 Depends: R (>= 2.10), affy (>= 1.23.4), limma Suggests: simpleaffy, R2HTML, affyPLM, hgu95av2cdf, hgu95av2, test3cdf, genefilter, estrogen, annaffy, gcrma License: LGPL MD5sum: 9c607fc29f8929be7b716b9118637b91 NeedsCompilation: no Title: Affymetrix Quality Assessment and Analysis Tool Description: The purpose of this package is to provide a comprehensive and easy-to-use tool for quality assessment and to identify differentially expressed genes in the Affymetrix gene expression data. biocViews: Microarray, OneChannel, QualityControl, Preprocessing, Bioinformatics, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Xiwei Wu , Xuejun Arthur Li Maintainer: Xuejun Arthur Li source.ver: src/contrib/AffyExpress_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AffyExpress_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AffyExpress_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AffyExpress_1.26.0.tgz vignettes: vignettes/AffyExpress/inst/doc/AffyExpress.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyExpress/inst/doc/AffyExpress.R Package: affyILM Version: 1.12.0 Depends: R (>= 2.10.0), methods, gcrma Imports: affxparser (>= 1.16.0), affy, graphics, methods, Biobase Suggests: AffymetrixDataTestFiles License: GPL version 3 MD5sum: b1d42eddcd56b3e8e144c2f37737ed29 NeedsCompilation: no Title: Linear Model of background subtraction and the Langmuir isotherm Description: affyILM is a preprocessing tool which estimates gene expression levels for Affymetrix Gene Chips. Input from physical chemistry is employed to first background subtract intensities before calculating concentrations on behalf of the Langmuir model. biocViews: Microarray, OneChannel, Preprocessing Author: K. Myriam Kroll, Fabrice Berger, Gerard Barkema, Enrico Carlon Maintainer: Myriam Kroll and Fabrice Berger source.ver: src/contrib/affyILM_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affyILM_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affyILM_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affyILM_1.12.0.tgz vignettes: vignettes/affyILM/inst/doc/affyILM.pdf vignetteTitles: affyILM1.3.0 hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyILM/inst/doc/affyILM.R Package: affyio Version: 1.28.0 Depends: R (>= 2.6.0), methods Imports: zlibbioc License: LGPL (>= 2) Archs: i386, x64 MD5sum: afbcf2d89651b96f6115c478c781e5ae NeedsCompilation: yes Title: Tools for parsing Affymetrix data files Description: Routines for parsing Affymetrix data files based upon file format information. Primary focus is on accessing the CEL and CDF file formats. biocViews: Microarray, DataImport, Infrastructure Author: Benjamin Milo Bolstad Maintainer: Benjamin Milo Bolstad source.ver: src/contrib/affyio_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affyio_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affyio_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affyio_1.28.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE dependsOnMe: affylmGUI, affyPara, makecdfenv, sscore importsMe: affy, crlmm, gcrma, oligo, oligoClasses suggestsMe: BufferedMatrixMethods Package: affylmGUI Version: 1.34.0 Depends: limma, tcltk, affy, BiocInstaller, affyio, affy, tkrplot, affyPLM, R2HTML, xtable, gcrma, affyPLM, AnnotationDbi License: LGPL MD5sum: 78d1f8e180599832bb79322f41374866 NeedsCompilation: no Title: GUI for affy analysis using limma package Description: A Graphical User Interface for affy analysis using the limma Microarray package biocViews: Microarray, OneChannel, DataImport, QualityControl, Preprocessing, Bioinformatics, DifferentialExpression, MultipleComparisons, GUI Author: James Wettenhall and Ken Simpson Division of Genetics and Bioinformatics, WEHI. Maintainer: Keith Satterley URL: http://bioinf.wehi.edu.au/affylmGUI/ source.ver: src/contrib/affylmGUI_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affylmGUI_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affylmGUI_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affylmGUI_1.34.0.tgz vignettes: vignettes/affylmGUI/inst/doc/affylmGUI.pdf, vignettes/affylmGUI/inst/doc/extract.pdf vignetteTitles: affylmGUI Vignette, Extracting affy and limma objects from affylmGUI files hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affylmGUI/inst/doc/affylmGUI.R, vignettes/affylmGUI/inst/doc/extract.R htmlDocs: vignettes/affylmGUI/inst/doc/about.html, vignettes/affylmGUI/inst/doc/CustMenu.html, vignettes/affylmGUI/inst/doc/index.html, vignettes/affylmGUI/inst/doc/windowsFocus.html htmlTitles: "About affylmGUI", "Customizing the menus in affylmGUI (for Advanced users)", "affylmGUI Documentation", "Troubleshooting Window Focus Problems" dependsOnMe: oneChannelGUI Package: affyPara Version: 1.20.0 Depends: R (>= 2.5.0), methods, affy (>= 1.20.0), snow (>= 0.2-3), vsn (>= 3.6.0), aplpack (>= 1.1.1), affyio Suggests: affydata Enhances: affy License: GPL-3 MD5sum: 35478ed50a1b8c4b468af63b9e512784 NeedsCompilation: no Title: Parallelized preprocessing methods for Affymetrix Oligonucleotide Arrays Description: The package contains parallelized functions for exploratory oligonucleotide array analysis. The package is designed for large numbers of microarray data. biocViews: Microarray, Preprocessing Author: Markus Schmidberger , Esmeralda Vicedo , Ulrich Mansmann Maintainer: Markus Schmidberger URL: http://www.ibe.med.uni-muenchen.de source.ver: src/contrib/affyPara_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affyPara_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affyPara_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affyPara_1.20.0.tgz vignettes: vignettes/affyPara/inst/doc/affyPara.pdf, vignettes/affyPara/inst/doc/vsnStudy.pdf vignetteTitles: Parallelized affy functions for preprocessing, Simulation Study for VSN Add-On Normalization and Subsample Size hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyPara/inst/doc/affyPara.R, vignettes/affyPara/inst/doc/vsnStudy.R Package: affypdnn Version: 1.34.0 Depends: R (>= 2.13.0), affy (>= 1.5) Suggests: affydata, hgu95av2probe License: LGPL MD5sum: 9762758d4fdf91d008633dece456c419 NeedsCompilation: no Title: Probe Dependent Nearest Neighbours (PDNN) for the affy package Description: The package contains functions to perform the PDNN method described by Li Zhang et al. biocViews: OneChannel, Microarray, Preprocessing Author: H. Bjorn Nielsen and Laurent Gautier (Many thanks to Li Zhang early communications about the existence of the PDNN program and related publications). Maintainer: Laurent Gautier source.ver: src/contrib/affypdnn_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affypdnn_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affypdnn_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affypdnn_1.34.0.tgz vignettes: vignettes/affypdnn/inst/doc/affypdnn.pdf vignetteTitles: affypdnn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affypdnn/inst/doc/affypdnn.R Package: affyPLM Version: 1.36.0 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), affy (>= 1.11.0), Biobase (>= 2.17.8), gcrma, stats, preprocessCore (>= 1.5.1) Imports: BiocGenerics, zlibbioc, graphics, grDevices, methods LinkingTo: preprocessCore Suggests: affydata, MASS License: GPL (>= 2) Archs: i386, x64 MD5sum: 920d5a904c7b7baa85bf96b76aa8c551 NeedsCompilation: yes Title: Methods for fitting probe-level models Description: A package that extends and improves the functionality of the base affy package. Routines that make heavy use of compiled code for speed. Central focus is on implementation of methods for fitting probe-level models and tools using these models. PLM based quality assessment tools. biocViews: Microarray, OneChannel, Preprocessing, QualityControl Author: Ben Bolstad Maintainer: Ben Bolstad URL: http://bmbolstad.com source.ver: src/contrib/affyPLM_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affyPLM_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affyPLM_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affyPLM_1.36.0.tgz vignettes: vignettes/affyPLM/inst/doc/AffyExtensions.pdf, vignettes/affyPLM/inst/doc/MAplots.pdf, vignettes/affyPLM/inst/doc/QualityAssess.pdf, vignettes/affyPLM/inst/doc/ThreeStep.pdf vignetteTitles: affyPLM: Fitting Probe Level Models, affyPLM: Advanced use of the MAplot function, affyPLM: Model Based QC Assessment of Affymetrix GeneChips, affyPLM: the threestep function hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyPLM/inst/doc/AffyExtensions.R, vignettes/affyPLM/inst/doc/MAplots.R, vignettes/affyPLM/inst/doc/QualityAssess.R, vignettes/affyPLM/inst/doc/ThreeStep.R dependsOnMe: affylmGUI, RefPlus importsMe: affyQCReport, arrayQualityMetrics, virtualArray suggestsMe: AffyExpress, arrayMvout, ArrayTools, BiocCaseStudies, BiocGenerics, frmaTools, ggbio, metahdep, oneChannelGUI, piano Package: affyQCReport Version: 1.38.0 Depends: Biobase (>= 1.13.16), affy, lattice Imports: affy, affyPLM, Biobase, genefilter, graphics, grDevices, lattice, RColorBrewer, simpleaffy, stats, utils, xtable Suggests: tkWidgets (>= 1.5.23), affydata (>= 1.4.1) License: LGPL (>= 2) MD5sum: 8be2e5660ef2575c1fc59516c44aa591 NeedsCompilation: no Title: QC Report Generation for affyBatch objects Description: This package creates a QC report for an AffyBatch object. The report is intended to allow the user to quickly assess the quality of a set of arrays in an AffyBatch object. biocViews: Microarray,OneChannel,QualityControl Author: Craig Parman , Conrad Halling , Robert Gentleman Maintainer: Craig Parman source.ver: src/contrib/affyQCReport_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/affyQCReport_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/affyQCReport_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/affyQCReport_1.38.0.tgz vignettes: vignettes/affyQCReport/inst/doc/affyQCReport.pdf vignetteTitles: affyQCReport: Methods for Generating Affymetrix QC Reports hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyQCReport/inst/doc/affyQCReport.R suggestsMe: BiocCaseStudies Package: AffyRNADegradation Version: 1.6.0 Depends: R (>= 2.9.0), methods, affy Suggests: AmpAffyExample License: GPL-2 MD5sum: 27e871d91ed78c990af004ea787206cc NeedsCompilation: no Title: Analyze and correct probe positional bias in microarray data due to RNA degradation Description: The package helps with the assessment and correction of RNA degradation effects in Affymetrix 3' expression arrays. The parameter d gives a robust and accurate measure of RNA integrity. The correction removes the probe positional bias, and thus improves comparability of samples that are affected by RNA degradation. biocViews: GeneExpression, Microarray, OneChannel, Preprocessing, QualityControl, Bioinformatics Author: Mario Fasold Maintainer: Mario Fasold source.ver: src/contrib/AffyRNADegradation_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AffyRNADegradation_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AffyRNADegradation_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AffyRNADegradation_1.6.0.tgz vignettes: vignettes/AffyRNADegradation/inst/doc/vignette.pdf vignetteTitles: AffyRNADegradation Example hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyRNADegradation/inst/doc/vignette.R Package: AffyTiling Version: 1.18.0 Depends: R (>= 2.6) Imports: affxparser, affy (>= 1.16), stats, utils, preprocessCore License: GPL (>= 2) Archs: i386, x64 MD5sum: 11c6b97fe1340340231e6c31eee89123 NeedsCompilation: yes Title: Easy extraction of individual probes in Affymetrix tiling arrays Description: This package provides easy, fast functions for the extraction and annotation of individual probes from Affymetrix tiling arrays. biocViews: Microarray, Preprocessing Author: Charles G. Danko Maintainer: Charles G. Danko source.ver: src/contrib/AffyTiling_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AffyTiling_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AffyTiling_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AffyTiling_1.18.0.tgz vignettes: vignettes/AffyTiling/inst/doc/AffyTiling.pdf vignetteTitles: AffyTiling hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyTiling/inst/doc/AffyTiling.R Package: AGDEX Version: 1.8.0 Depends: R (>= 2.10), Biobase, GSEABase Imports: stats License: GPL Version 2 or later MD5sum: c5dd4427e7b90797e783b97b1551680c NeedsCompilation: no Title: Agreement of Differential Expression Analysis Description: A tool to evaluate agreement of differential expression for cross-species genomics biocViews: Microarray, Genetics, Bioinformatics, GeneExpression Author: Stan Pounds ; Cuilan Lani Gao Maintainer: Cuilan lani Gao source.ver: src/contrib/AGDEX_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AGDEX_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AGDEX_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AGDEX_1.8.0.tgz vignettes: vignettes/AGDEX/inst/doc/AGDEX.pdf vignetteTitles: AGDEX.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AGDEX/inst/doc/AGDEX.R Package: Agi4x44PreProcess Version: 1.20.0 Depends: R (>= 2.10), Biobase, limma, annotate, genefilter Suggests: vsn, affycoretools, hgug4112a.db, GO.db, marray, gplots, gtools, gdata License: GPL-3 MD5sum: 2dc30cf935e6317bfb2879f3a688f904 NeedsCompilation: no Title: PreProcessing of Agilent 4x44 array data Description: Preprocessing of Agilent 4x44 array data biocViews: Microarray, OneChannel, Preprocessing Author: Pedro Lopez-Romero Maintainer: Pedro Lopez-Romero source.ver: src/contrib/Agi4x44PreProcess_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Agi4x44PreProcess_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Agi4x44PreProcess_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Agi4x44PreProcess_1.20.0.tgz vignettes: vignettes/Agi4x44PreProcess/inst/doc/Agi4x44PreProcess.pdf vignetteTitles: Agi4x44PreProcess hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Agi4x44PreProcess/inst/doc/Agi4x44PreProcess.R Package: agilp Version: 3.2.0 Depends: R (>= 2.14.0) License: GPL-3 MD5sum: 60e765a4a2a330e15fd00c2a4767c7e3 NeedsCompilation: no Title: Agilent expression array processing package Description: provides a pipeline for the low-level analysis of gene expression microarray data, primarily Agilent data Author: Benny Chain Maintainer: Benny Chain source.ver: src/contrib/agilp_3.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/agilp_3.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/agilp_3.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/agilp_3.2.0.tgz vignettes: vignettes/agilp/inst/doc/agilp_manual.pdf vignetteTitles: An R Package for processing expression microarray data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/agilp/inst/doc/agilp_manual.R Package: AgiMicroRna Version: 2.10.0 Depends: R (>= 2.10),methods,Biobase,limma,affy (>= 1.22),preprocessCore,affycoretools Imports: Biobase Suggests: geneplotter,marray,gplots,gtools,gdata,codelink License: GPL-3 MD5sum: 30dc022709fc82e790e8768861d73dc9 NeedsCompilation: no Title: Processing and Differential Expression Analysis of Agilent microRNA chips Description: Processing and Analysis of Agilent microRNA data biocViews: Microarray,AgilentChip,OneChannel,Preprocessing,DifferentialExpression,Bioinformatics Author: Pedro Lopez-Romero Maintainer: Pedro Lopez-Romero source.ver: src/contrib/AgiMicroRna_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AgiMicroRna_2.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AgiMicroRna_2.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AgiMicroRna_2.10.0.tgz vignettes: vignettes/AgiMicroRna/inst/doc/AgiMicroRna.pdf vignetteTitles: AgiMicroRna hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AgiMicroRna/inst/doc/AgiMicroRna.R Package: altcdfenvs Version: 2.22.0 Depends: R (>= 2.7), methods, BiocGenerics (>= 0.1.0), Biobase (>= 2.15.1), affy, makecdfenv, Biostrings, hypergraph Suggests: plasmodiumanophelescdf, hgu95acdf, hgu133aprobe, hgu133a.db, hgu133acdf, Rgraphviz, RColorBrewer License: GPL (>= 2) MD5sum: 15fdd6f0dcabb209685f8380dd28e710 NeedsCompilation: no Title: alternative CDF environments (aka probeset mappings) Description: Convenience data structures and functions to handle cdfenvs biocViews: Microarray, OneChannel, QualityControl, Preprocessing, Annotation, ProprietaryPlatforms, Transcription Author: Laurent Gautier Maintainer: Laurent Gautier source.ver: src/contrib/altcdfenvs_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/altcdfenvs_2.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/altcdfenvs_2.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/altcdfenvs_2.22.0.tgz vignettes: vignettes/altcdfenvs/inst/doc/altcdfenvs.pdf, vignettes/altcdfenvs/inst/doc/modify.pdf, vignettes/altcdfenvs/inst/doc/ngenomeschips.pdf vignetteTitles: altcdfenvs, affy primer, affy primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/altcdfenvs/inst/doc/altcdfenvs.R, vignettes/altcdfenvs/inst/doc/modify.R, vignettes/altcdfenvs/inst/doc/ngenomeschips.R importsMe: Harshlight Package: annaffy Version: 1.32.0 Depends: R (>= 2.5.0), methods, Biobase, GO.db, KEGG.db Imports: AnnotationDbi (>= 0.1.15) Suggests: hgu95av2.db, multtest, tcltk License: LGPL MD5sum: e7e07a1569112488c61a9cb4da7e4390 NeedsCompilation: no Title: Annotation tools for Affymetrix biological metadata Description: Functions for handling data from Bioconductor Affymetrix annotation data packages. Produces compact HTML and text reports including experimental data and URL links to many online databases. Allows searching biological metadata using various criteria. biocViews: OneChannel, Microarray, Annotation, GO, Pathways, ReportWriting Author: Colin A. Smith Maintainer: Colin A. Smith source.ver: src/contrib/annaffy_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/annaffy_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/annaffy_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/annaffy_1.32.0.tgz vignettes: vignettes/annaffy/inst/doc/annaffy.pdf vignetteTitles: annaffy Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annaffy/inst/doc/annaffy.R dependsOnMe: a4Base, a4Reporting, PGSEA, webbioc importsMe: affycoretools suggestsMe: AffyExpress, ArrayTools, BiocCaseStudies, maDB Package: annmap Version: 1.2.1 Depends: R (>= 2.15.0), methods, GenomicRanges Imports: DBI, RMySQL (>= 0.6-0), digest, Biobase, grid, lattice, Rsamtools, genefilter, IRanges, BiocGenerics Suggests: RUnit, rjson License: GPL-2 MD5sum: 602b6a4e58ce7adf812f637e9185b2e0 NeedsCompilation: no Title: Genome annotation and visualisation package pertaining to Affymetrix arrays and NGS analysis. Description: annmap provides annotation mappings for Affymetrix exon arrays and coordinate based queries to support deep sequencing data analysis. Database access is hidden behind the API which provides a set of functions such as genesInRange(), geneToExon(), exonDetails(), etc. Functions to plot gene architecture and BAM file data are also provided. Underlying data are from Ensembl. biocViews: Annotation, Bioinformatics, Microarray, OneChannel, ReportWriting, Transcription, Visualization Author: Tim Yates Maintainer: Tim Yates URL: http://annmap.picr.man.ac.uk source.ver: src/contrib/annmap_1.2.1.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/annmap_1.2.1.tgz vignettes: vignettes/annmap/inst/doc/annmap.pdf, vignettes/annmap/inst/doc/cookbook.pdf, vignettes/annmap/inst/doc/INSTALL.pdf vignetteTitles: annmap primer, The Annmap Cookbook, annmap installation instruction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annmap/inst/doc/annmap.R, vignettes/annmap/inst/doc/cookbook.R, vignettes/annmap/inst/doc/INSTALL.R Package: annotate Version: 1.38.0 Depends: R (>= 2.10), AnnotationDbi (>= 0.1.15) Imports: Biobase, AnnotationDbi, DBI, xtable, graphics, utils, stats, methods, XML (>= 0.92-2), BiocGenerics (>= 0.1.13) Suggests: Biobase, hgu95av2.db, genefilter, Biostrings (>= 2.25.10), rae230a.db, rae230aprobe, tkWidgets, GO.db, org.Hs.eg.db, XML (>= 0.92-2), org.Mm.eg.db, hom.Hs.inp.db, humanCHRLOC, Rgraphviz, RUnit, License: Artistic-2.0 MD5sum: 3080c62022743b39bd4cdd974a91b165 NeedsCompilation: no Title: Annotation for microarrays Description: Using R enviroments for annotation. biocViews: Annotation, Pathways, GO Author: R. Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/annotate_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/annotate_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/annotate_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/annotate_1.38.0.tgz vignettes: vignettes/annotate/inst/doc/annotate.pdf, vignettes/annotate/inst/doc/chromLoc.pdf, vignettes/annotate/inst/doc/GOusage.pdf, vignettes/annotate/inst/doc/prettyOutput.pdf, vignettes/annotate/inst/doc/query.pdf, vignettes/annotate/inst/doc/useDataPkgs.pdf, vignettes/annotate/inst/doc/useHomology.pdf, vignettes/annotate/inst/doc/useProbeInfo.pdf vignetteTitles: Annotation Overview, HowTo: use chromosomal information, Basic GO Usage, HowTo: Get HTML Output, HOWTO: Use the online query tools, Using Data Packages, Using the homology package, Using Affymetrix Probe Level Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annotate/inst/doc/annotate.R, vignettes/annotate/inst/doc/chromLoc.R, vignettes/annotate/inst/doc/GOusage.R, vignettes/annotate/inst/doc/prettyOutput.R, vignettes/annotate/inst/doc/query.R, vignettes/annotate/inst/doc/useDataPkgs.R, vignettes/annotate/inst/doc/useHomology.R, vignettes/annotate/inst/doc/useProbeInfo.R dependsOnMe: Agi4x44PreProcess, ChromHeatMap, GeneAnswers, geneplotter, GSEABase, idiogram, macat, MineICA, MLInterfaces, PCpheno, phenoTest, PREDA, RpsiXML, ScISI importsMe: affycoretools, Category, categoryCompare, ChromHeatMap, codelink, DrugVsDisease, gCMAP, gCMAPWeb, GeneAnswers, genefilter, GeneGroupAnalysis, geneplotter, GlobalAncova, globaltest, GOstats, GSEABase, lumi, methyAnalysis, methylumi, phenoTest, qpgraph, ScISI, splicegear, tigre suggestsMe: BiocCaseStudies, biomaRt, geneplotter, GlobalAncova, globaltest, GOstats, GSEAlm, maigesPack, metagenomeSeq, MLP, oneChannelGUI, puma, siggenes, tigre Package: AnnotationDbi Version: 1.22.6 Depends: R (>= 2.7.0), methods, utils, BiocGenerics (>= 0.5.4), Biobase (>= 1.17.0) Imports: methods, utils, DBI, RSQLite, BiocGenerics, Biobase, IRanges Suggests: DBI (>= 0.2-4), RSQLite (>= 0.6-4), hgu95av2.db, GO.db, org.Sc.sgd.db, org.At.tair.db, KEGG.db, RUnit, TxDb.Hsapiens.UCSC.hg19.knownGene, hom.Hs.inp.db, org.Hs.eg.db, seqnames.db, reactome.db, AnnotationForge, graph License: Artistic-2.0 MD5sum: e1f16372e99da79399d5b459aed32123 NeedsCompilation: no Title: Annotation Database Interface Description: Provides user interface and database connection code for annotation data packages using SQLite data storage. biocViews: Annotation, Infrastructure Author: Herve Pages, Marc Carlson, Seth Falcon, Nianhua Li Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/AnnotationDbi_1.22.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/AnnotationDbi_1.22.6.zip win64.binary.ver: bin/windows64/contrib/2.16/AnnotationDbi_1.22.6.zip mac.binary.ver: bin/macosx/contrib/2.16/AnnotationDbi_1.22.6.tgz vignettes: vignettes/AnnotationDbi/inst/doc/AnnotationDbi.pdf, vignettes/AnnotationDbi/inst/doc/databaseTypes.pdf, vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.pdf vignetteTitles: How to use bimaps from the ".db" annotation packages, databaseTypes.pdf, AnnotationDbi: Introduction To Bioconductor Annotation Packages hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationDbi/inst/doc/AnnotationDbi.R, vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.R dependsOnMe: a4Base, a4Preproc, affylmGUI, annotate, AnnotationForge, AnnotationFuncs, attract, Category, categoryCompare, chimera, ChromHeatMap, eisa, ExpressionView, GenomicFeatures, GOFunction, goProfiles, MLP, OrganismDbi, PADOG, PAnnBuilder, pathRender, PGSEA, Resourcerer, RpsiXML, safe, topGO importsMe: adSplit, affycoretools, annaffy, annotate, AnnotationHub, attract, beadarray, BioNet, CancerMutationAnalysis, Category, categoryCompare, ChIPpeakAnno, ChromHeatMap, clusterProfiler, CoCiteStats, domainsignatures, DOSE, ExpressionView, FunciSNP, gCMAP, gCMAPWeb, genefilter, GeneGroupAnalysis, geneplotter, GGBase, GGtools, GlobalAncova, globaltest, GOFunction, GOSemSim, goseq, GOstats, goTools, graphite, GSEABase, Gviz, HTSanalyzeR, KEGGprofile, lumi, methyAnalysis, methylumi, MineICA, MiRaGE, OrganismDbi, PADOG, PAnnBuilder, pathview, pcaGoPromoter, PCpheno, phenoTest, qpgraph, ReactomePA, REDseq, ScISI, SLGI, tigre, topGO, UniProt.ws, VariantAnnotation, virtualArray suggestsMe: BiocCaseStudies, BiocGenerics, GeneAnswers, GeneRegionScan, GenomicRanges, MmPalateMiRNA, oneChannelGUI, sigPathway Package: AnnotationForge Version: 1.2.2 Depends: R (>= 2.7.0), methods, utils, BiocGenerics (>= 0.1.13), Biobase (>= 1.17.0), AnnotationDbi (>= 1.19.15), org.Hs.eg.db Imports: methods, utils, DBI, RSQLite, BiocGenerics, Biobase Suggests: DBI (>= 0.2-4), RSQLite (>= 0.6-4), XML, RCurl, hgu95av2.db, human.db0, affy, Homo.sapiens, hom.Hs.inp.db, GO.db License: Artistic-2.0 MD5sum: 43590d2969fc1dba795fb46ff27d3b00 NeedsCompilation: no Title: Code for Building Annotation Database Packages Description: Provides code for generating Annotation packages and their databases. Packages produced are intended to be used with AnnotationDbi. biocViews: Annotation, Infrastructure Author: Marc Carlson, Herve Pages Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/AnnotationForge_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/AnnotationForge_1.2.2.zip win64.binary.ver: bin/windows64/contrib/2.16/AnnotationForge_1.2.2.zip mac.binary.ver: bin/macosx/contrib/2.16/AnnotationForge_1.2.2.tgz vignettes: vignettes/AnnotationForge/inst/doc/Homo_sapiens.pdf, vignettes/AnnotationForge/inst/doc/makeProbePackage.pdf, vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.pdf, vignettes/AnnotationForge/inst/doc/NewSchema.pdf, vignettes/AnnotationForge/inst/doc/SQLForge.pdf vignetteTitles: Homo_sapiens.pdf, Creating probe packages, AnnotationForge: Creating select Interfaces for custom Annotation resources, Creating an annotation package with a new database schema, SQLForge: An easy way to create a new annotation package with a standard database schema. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationForge/inst/doc/makeProbePackage.R, vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.R, vignettes/AnnotationForge/inst/doc/NewSchema.R, vignettes/AnnotationForge/inst/doc/SQLForge.R importsMe: GOstats, methylumi suggestsMe: AnnotationDbi Package: AnnotationFuncs Version: 1.10.0 Depends: R (>= 2.7.0), AnnotationDbi Suggests: org.Bt.eg.db, GO.db, org.Hs.eg.db, hom.Hs.inp.db License: GPL-2 MD5sum: 650525e99eb9ac286e07c48c04a8422b NeedsCompilation: no Title: Annotation translation functions Description: Functions for handling translating between different identifieres using the Biocore Data Team data-packages (e.g. org.Bt.eg.db). biocViews: AnnotationData, Software Author: Stefan McKinnon Edwards Maintainer: Stefan McKinnon Edwards URL: http://www.iysik.com/index.php?page=annotation-functions source.ver: src/contrib/AnnotationFuncs_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/AnnotationFuncs_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/AnnotationFuncs_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/AnnotationFuncs_1.10.0.tgz vignettes: vignettes/AnnotationFuncs/inst/doc/AnnotationFuncsUserguide.pdf vignetteTitles: Annotation mapping functions hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: AnnotationHub Version: 1.0.2 Depends: IRanges Imports: methods, stats, utils, rjson, BiocGenerics, BiocInstaller (>= 1.10.0), AnnotationDbi, GenomicRanges Suggests: RUnit, RCurl, Rsamtools License: Artistic-2.0 MD5sum: cb67b5d5f21621c5d61b1dc5aea0f1dc NeedsCompilation: no Title: A client for retrieving Bioconductor objects from AnnotationHub Description: A client for retrieving data from the Bioconductor AnnotationHub online services. biocViews: Annotation, Infrastructure Author: Marc Carlson Maintainer: Marc Carlson source.ver: src/contrib/AnnotationHub_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/AnnotationHub_1.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/AnnotationHub_1.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/AnnotationHub_1.0.2.tgz vignettes: vignettes/AnnotationHub/inst/doc/AnnotationHub.pdf vignetteTitles: AnnotationHub: A client package for retrieving data from the AnnotationHub web service hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationHub/inst/doc/AnnotationHub.R Package: annotationTools Version: 1.34.0 Imports: Biobase, stats License: GPL MD5sum: ab2dc88fb9e604918967368df66b9ae7 NeedsCompilation: no Title: Annotate microarrays and perform cross-species gene expression analyses using flat file databases. Description: Functions to annotate microarrays, find orthologs, and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file database (plain text files). biocViews: Microarray, Annotation Author: Alexandre Kuhn Maintainer: Alexandre Kuhn source.ver: src/contrib/annotationTools_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/annotationTools_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/annotationTools_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/annotationTools_1.34.0.tgz vignettes: vignettes/annotationTools/inst/doc/annotationTools.pdf vignetteTitles: annotationTools Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annotationTools/inst/doc/annotationTools.R Package: anota Version: 1.8.0 Depends: qvalue Imports: multtest, qvalue License: GPL-3 MD5sum: d6f65774cd07cd846ae80c14e35edde3 NeedsCompilation: no Title: ANalysis Of Translational Activity (ANOTA). Description: Genome wide studies of translational control is emerging as a tool to study verious biological conditions. The output from such analysis is both the mRNA level (e.g. cytosolic mRNA level) and the levl of mRNA actively involved in translation (the actively translating mRNA level) for each mRNA. The standard analysis of such data strives towards identifying differential translational between two or more sample classes - i.e. differences in actively translated mRNA levels that are independent of underlying differences in cytosolic mRNA levels. This package allows for such analysis using partial variances and the random variance model. As 10s of thousands of mRNAs are analyzed in parallell the library performs a number of tests to assure that the data set is suitable for such analysis. biocViews: GeneExpression, DifferentialExpression, Microarray, HighThroughputSequencing Author: Ola Larsson , Nahum Sonenberg , Robert Nadon Maintainer: Ola Larsson source.ver: src/contrib/anota_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/anota_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/anota_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/anota_1.8.0.tgz vignettes: vignettes/anota/inst/doc/anota.pdf vignetteTitles: ANalysis Of Translational Activity (anota) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/anota/inst/doc/anota.R Package: antiProfiles Version: 1.0.0 Depends: R (>= 3.0), matrixStats (>= 0.5), methods (>= 2.14), Suggests: antiProfilesData, RColorBrewer License: Artistic-2.0 MD5sum: 3a12289e77d7bdbdcb1ff49d43a291b3 NeedsCompilation: no Title: Implementation of gene expression anti-profiles Description: Implements gene expression anti-profiles as described in Corrada Bravo et al., BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272. biocViews: GeneExpression,Classification Author: Hector Corrada Bravo, Rafael A. Irizarry and Jeffrey T. Leek Maintainer: Hector Corrada Bravo source.ver: src/contrib/antiProfiles_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/antiProfiles_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/antiProfiles_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/antiProfiles_1.0.0.tgz vignettes: vignettes/antiProfiles/inst/doc/antiProfiles.pdf vignetteTitles: Introduction to antiProfiles hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/antiProfiles/inst/doc/antiProfiles.R Package: apComplex Version: 2.26.0 Depends: R (>= 2.10), graph, RBGL Imports: Rgraphviz, stats, org.Sc.sgd.db License: LGPL MD5sum: 0fe68e4e89d47fd68cecdbb6abce74b4 NeedsCompilation: no Title: Estimate protein complex membership using AP-MS protein data Description: Functions to estimate a bipartite graph of protein complex membership using AP-MS data. biocViews: NetworkInference, MassSpectrometry, GraphsAndNetworks Author: Denise Scholtens Maintainer: Denise Scholtens source.ver: src/contrib/apComplex_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/apComplex_2.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/apComplex_2.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/apComplex_2.26.0.tgz vignettes: vignettes/apComplex/inst/doc/apComplex.pdf vignetteTitles: apComplex hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/apComplex/inst/doc/apComplex.R dependsOnMe: ScISI suggestsMe: BiocCaseStudies Package: aroma.light Version: 1.30.5 Depends: R (>= 2.10.0), matrixStats (>= 0.5.3) Imports: R.methodsS3 (>= 1.4.2) Suggests: R.oo (>= 1.9.9), R.utils (>= 1.16.2), princurve (>= 1.1-11) License: GPL (>= 2) MD5sum: 6b9a9327e1fb305f1b0c05afa27b06d2 NeedsCompilation: no Title: Light-weight methods for normalization and visualization of microarray data using only basic R data types Description: Methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes. biocViews: Infrastructure, Microarray, OneChannel, TwoChannel, MultiChannel, Visualization, Preprocessing Author: Henrik Bengtsson, Pierre Neuvial Maintainer: Henrik Bengtsson URL: http://www.aroma-project.org/ source.ver: src/contrib/aroma.light_1.30.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/aroma.light_1.30.5.zip win64.binary.ver: bin/windows64/contrib/2.16/aroma.light_1.30.5.zip mac.binary.ver: bin/macosx/contrib/2.16/aroma.light_1.30.5.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: EDASeq Package: ArrayExpress Version: 1.20.0 Depends: R (>= 2.9.0), Biobase (>= 2.4.0) Imports: XML, affy, limma License: Artistic-2.0 MD5sum: 123824fafa9e59060b9f3b74257f5bb8 NeedsCompilation: no Title: Access the ArrayExpress Microarray Database at EBI and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet Description: Access the ArrayExpress Repository at EBI and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet biocViews: Microarray, DataImport, OneChannel, TwoChannel Author: Audrey Kauffmann, Ibrahim Emam Maintainer: Ibrahim Emam source.ver: src/contrib/ArrayExpress_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ArrayExpress_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ArrayExpress_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ArrayExpress_1.20.0.tgz vignettes: vignettes/ArrayExpress/inst/doc/ArrayExpress.pdf vignetteTitles: ArrayExpress: Import and convert ArrayExpress data sets into R object hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayExpress/inst/doc/ArrayExpress.R dependsOnMe: DrugVsDisease suggestsMe: gCMAPWeb Package: ArrayExpressHTS Version: 1.10.0 Depends: sampling, Rsamtools (>= 1.3.32), snow Imports: Biobase, Biostrings, DESeq, GenomicRanges, Hmisc, IRanges, R2HTML, RColorBrewer, Rsamtools, ShortRead, XML, biomaRt, edgeR, grDevices, graphics, methods, rJava, stats, svMisc, utils, sendmailR, bitops LinkingTo: Rsamtools License: Artistic License 2.0 MD5sum: 871c864995c6061e86a721eacd3b75d9 NeedsCompilation: yes Title: ArrayExpress High Throughput Sequencing Processing Pipeline Description: RNA-Seq processing pipeline for public ArrayExpress experiments or local datasets biocViews: RNAseq, Sequencing, HighThroughputSequencing Author: Angela Goncalves, Andrew Tikhonov Maintainer: Angela Goncalves , Andrew Tikhonov source.ver: src/contrib/ArrayExpressHTS_1.10.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/ArrayExpressHTS_1.10.0.tgz vignettes: vignettes/ArrayExpressHTS/inst/doc/ArrayExpressHTS.pdf vignetteTitles: ArrayExpressHTS: RNA-Seq Pipeline for transcription profiling experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayExpressHTS/inst/doc/ArrayExpressHTS.R Package: arrayMvout Version: 1.18.0 Depends: R (>= 2.6.0), tools, methods, utils, parody, Biobase, affy, lumi Imports: simpleaffy, mdqc, affyContam, Suggests: MAQCsubset, mvoutData, lumiBarnes, affyPLM, affydata, hgu133atagcdf License: Artistic-2.0 MD5sum: edf848eb7320e999745af5cf44f271c1 NeedsCompilation: no Title: multivariate outlier detection for expression array QA Description: This package supports the application of diverse quality metrics to AffyBatch instances, summarizing these metrics via PCA, and then performing parametric outlier detection on the PCs to identify aberrant arrays with a fixed Type I error rate biocViews: Infrastructure, Bioinformatics, Microarray, QualityControl Author: Z. Gao, A. Asare, R. Wang, V. Carey Maintainer: V. Carey source.ver: src/contrib/arrayMvout_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/arrayMvout_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/arrayMvout_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/arrayMvout_1.18.0.tgz vignettes: vignettes/arrayMvout/inst/doc/arrayMvout-asdad.pdf, vignettes/arrayMvout/inst/doc/arrayMvout-lkadas.pdf, vignettes/arrayMvout/inst/doc/arrayMvout-lkda.pdf, vignettes/arrayMvout/inst/doc/arrayMvout.pdf vignetteTitles: arrayMvout-asdad.pdf, arrayMvout-lkadas.pdf, arrayMvout-lkda.pdf, arrayMvout -- multivariate outlier algorithm for expression arrays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/arrayMvout/inst/doc/arrayMvout.R Package: arrayQuality Version: 1.38.0 Depends: R (>= 2.2.0) Imports: graphics, grDevices, grid, gridBase, hexbin, limma, marray, methods, RColorBrewer, stats, utils Suggests: mclust, MEEBOdata, HEEBOdata License: LGPL MD5sum: d73fad2dd8b2198deac0aa550a5c1ecf NeedsCompilation: no Title: Assessing array quality on spotted arrays Description: Functions for performing print-run and array level quality assessment. biocViews: Microarray,TwoChannel,QualityControl,Visualization Author: Agnes Paquet and Jean Yee Hwa Yang Maintainer: Agnes Paquet URL: http://arrays.ucsf.edu/ source.ver: src/contrib/arrayQuality_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/arrayQuality_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/arrayQuality_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/arrayQuality_1.38.0.tgz vignettes: vignettes/arrayQuality/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE htmlDocs: vignettes/arrayQuality/inst/doc/basicQuality.html, vignettes/arrayQuality/inst/doc/customQuality.html, vignettes/arrayQuality/inst/doc/index.html, vignettes/arrayQuality/inst/doc/print-runQC.html htmlTitles: "arrayQuality User Manual", "customQuality", "arrayQuality User's guide", "print-run qc" Package: arrayQualityMetrics Version: 3.16.0 Imports: affy, affyPLM (>= 1.27.3), beadarray, Biobase, Cairo (>= 1.4-6), genefilter, graphics, grDevices, grid, Hmisc, hwriter, lattice, latticeExtra, limma, methods, RColorBrewer, setRNG, simpleaffy, stats, SVGAnnotation (>= 0.9-0), utils, vsn (>= 3.23.3), XML Suggests: ALLMLL, CCl4 License: LGPL (>= 2) MD5sum: 1a2ca974244f890eb2affb12db60369d NeedsCompilation: no Title: Quality metrics on microarray data sets Description: This package generates microarray quality metrics reports for data in Bioconductor microarray data containers (ExpressionSet, NChannelSet, AffyBatch). Report contain both general and platform-specific sections. Both one and two color array platforms are supported. biocViews: Microarray, QualityControl, OneChannel, TwoChannel, ReportWriting Author: Audrey Kauffmann, Wolfgang Huber Maintainer: Audrey Kauffmann source.ver: src/contrib/arrayQualityMetrics_3.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/arrayQualityMetrics_3.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/arrayQualityMetrics_3.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/arrayQualityMetrics_3.16.0.tgz vignettes: vignettes/arrayQualityMetrics/inst/doc/aqm.pdf, vignettes/arrayQualityMetrics/inst/doc/arrayQualityMetrics.pdf vignetteTitles: Advanced topics: Customizing arrayQualityMetrics reports and programmatic processing of the output, Introduction: microarray quality assessment with arrayQualityMetrics hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/arrayQualityMetrics/inst/doc/aqm.R, vignettes/arrayQualityMetrics/inst/doc/arrayQualityMetrics.R Package: ArrayTools Version: 1.20.0 Depends: R (>= 2.7.0), affy (>= 1.23.4), Biobase (>= 2.5.5), methods Imports: affy, Biobase, graphics, grDevices, limma, methods, stats, utils, xtable Suggests: simpleaffy, R2HTML, affydata, affyPLM, genefilter, annaffy, gcrma, hugene10sttranscriptcluster.db License: LGPL (>= 2.0) MD5sum: 7cc95a627569afc7f34fe93bd354e829 NeedsCompilation: no Title: geneChip Analysis Package Description: This package is designed to provide solutions for quality assessment and to detect differentially expressed genes for the Affymetrix GeneChips, including both 3' -arrays and gene 1.0-ST arrays. The package generates comprehensive analysis reports in HTML format. Hyperlinks on the report page will lead to a series of QC plots, processed data, and differentially expressed gene lists. Differentially expressed genes are reported in tabular format with annotations hyperlinked to online biological databases. biocViews: Microarray, OneChannel, QualityControl, Preprocessing, Statistics, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Xiwei Wu, Arthur Li Maintainer: Arthur Li source.ver: src/contrib/ArrayTools_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ArrayTools_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ArrayTools_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ArrayTools_1.20.0.tgz vignettes: vignettes/ArrayTools/inst/doc/ArrayTools.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayTools/inst/doc/ArrayTools.R Package: ARRmNormalization Version: 1.0.0 Depends: R (>= 2.15.1), ARRmData License: Artistic-2.0 MD5sum: 38e9ef9a52f10a16dd9f9ef1c1f991b0 NeedsCompilation: no Title: Adaptive Robust Regression normalization for Illumina methylation data Description: Perform the Adaptive Robust Regression method (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay. biocViews: DNAMethylation, TwoChannel, Preprocessing, Microarray Author: Jean-Philippe Fortin, Celia M.T. Greenwood, Aurelie Labbe. Maintainer: Jean-Philippe Fortin source.ver: src/contrib/ARRmNormalization_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ARRmNormalization_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ARRmNormalization_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ARRmNormalization_1.0.0.tgz vignettes: vignettes/ARRmNormalization/inst/doc/ARRmNormalization.pdf vignetteTitles: ARRmNormalization hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ARRmNormalization/inst/doc/ARRmNormalization.R Package: ASEB Version: 1.4.0 Depends: R (>= 2.8.0), methods Imports: graphics, methods, utils License: GPL (>= 3) Archs: i386, x64 MD5sum: 49ede68dbc90a5cc81d0fd118df08d73 NeedsCompilation: yes Title: Predict Acetylated Lysine Sites Description: ASEB is an R package to predict lysine sites that can be acetylated by a specific KAT-family. biocViews: Proteomics Author: Likun Wang and Tingting Li . Maintainer: Likun Wang source.ver: src/contrib/ASEB_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ASEB_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ASEB_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ASEB_1.4.0.tgz vignettes: vignettes/ASEB/inst/doc/ASEB.pdf vignetteTitles: ASEB hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ASEB/inst/doc/ASEB.R Package: attract Version: 1.12.0 Depends: R (>= 2.10.0), AnnotationDbi, KEGG.db, limma, cluster, GOstats, graphics, methods, stats Imports: Biobase, AnnotationDbi, KEGG.db, limma, cluster, GOstats, graphics, methods, stats Suggests: illuminaHumanv1.db License: LGPL (>= 2.0) MD5sum: b1321e064cad4f12611b518f4890313a NeedsCompilation: no Title: Methods to Find the Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape Description: This package contains the functions to find the gene expression modules that represent the drivers of Kauffman's attractor landscape. The modules are the core attractor pathways that discriminate between different cell types of groups of interest. Each pathway has a set of synexpression groups, which show transcriptionally-coordinated changes in gene expression. biocViews: Statistics, GeneExpression Author: Jessica Mar Maintainer: Jessica Mar source.ver: src/contrib/attract_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/attract_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/attract_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/attract_1.12.0.tgz vignettes: vignettes/attract/inst/doc/attract.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/attract/inst/doc/attract.R Package: BAC Version: 1.20.0 Depends: R (>= 2.10) License: Artistic-2.0 Archs: i386, x64 MD5sum: e860552648093bee22dd50381395f4b7 NeedsCompilation: yes Title: Bayesian Analysis of Chip-chip experiment Description: This package uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments biocViews: Microarray,Transcription,Bioinformatics Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/BAC_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BAC_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BAC_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BAC_1.20.0.tgz vignettes: vignettes/BAC/inst/doc/BAC.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BAC/inst/doc/BAC.R Package: BaseSpaceR Version: 1.0.1 Depends: R (>= 2.15.0), methods, RCurl, RJSONIO Imports: methods Suggests: RUnit License: Apache License 2.0 MD5sum: 7fb29e47dae2c7f11cde6b3031f4ca2f NeedsCompilation: no Title: R SDK for BaseSpace RESTful API Description: A rich R interface to Illumina's BaseSpace cloud computing environment, enabling the fast development of data analysis and visualisation tools. biocViews: Infrastructure, DataRepresentation, ConnectTools, Software, DataImport, HighThroughputSequencing, Sequencing, Genetics Author: Adrian Alexa Maintainer: Adrian Alexa source.ver: src/contrib/BaseSpaceR_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/BaseSpaceR_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/BaseSpaceR_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/BaseSpaceR_1.0.1.tgz vignettes: vignettes/BaseSpaceR/inst/doc/BaseSpaceR.pdf, vignettes/BaseSpaceR/inst/doc/BaseSpaceR-QscoreApp.pdf vignetteTitles: BaseSpaceR, BaseSpaceR-QscoreApp.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BaseSpaceR/inst/doc/BaseSpaceR.R Package: BayesPeak Version: 1.12.0 Depends: R (>= 2.14), IRanges Imports: IRanges, graphics License: GPL (>= 2) Archs: i386, x64 MD5sum: 2c6eb4f8b9e87b42870928ccf0118294 NeedsCompilation: yes Title: Bayesian Analysis of ChIP-seq Data Description: This package is an implementation of the BayesPeak algorithm for peak-calling in ChIP-seq data. biocViews: ChIPseq Author: Christiana Spyrou, Jonathan Cairns, Rory Stark, Andy Lynch, Simon Tavar\\'{e}, Maintainer: Jonathan Cairns source.ver: src/contrib/BayesPeak_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BayesPeak_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BayesPeak_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BayesPeak_1.12.0.tgz vignettes: vignettes/BayesPeak/inst/doc/BayesPeak.pdf, vignettes/BayesPeak/inst/doc/regionOFdiag.pdf vignetteTitles: BayesPeak Vignette, regionOFdiag.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BayesPeak/inst/doc/BayesPeak.R Package: baySeq Version: 1.14.1 Depends: R (>= 2.3.0), methods Suggests: snow, edgeR License: GPL-3 MD5sum: ff8600948289ed17830334bdbe871810 NeedsCompilation: no Title: Empirical Bayesian analysis of patterns of differential expression in count data Description: This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods. biocViews: Bioinformatics, HighThroughputSequencing, DifferentialExpression, MultipleComparisons, SAGE Author: Thomas J. Hardcastle Maintainer: Thomas J. Hardcastle source.ver: src/contrib/baySeq_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/baySeq_1.14.1.zip win64.binary.ver: bin/windows64/contrib/2.16/baySeq_1.14.1.zip mac.binary.ver: bin/macosx/contrib/2.16/baySeq_1.14.1.tgz vignettes: vignettes/baySeq/inst/doc/baySeq.pdf vignetteTitles: baySeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/baySeq/inst/doc/baySeq.R dependsOnMe: Rcade, segmentSeq importsMe: segmentSeq suggestsMe: oneChannelGUI Package: BCRANK Version: 1.22.0 Depends: methods Imports: Biostrings Suggests: seqLogo License: GPL-2 Archs: i386, x64 MD5sum: aa0557f522a1bf942696c0b53729ee74 NeedsCompilation: yes Title: Predicting binding site consensus from ranked DNA sequences Description: Functions and classes for de novo prediction of transcription factor binding consensus by heuristic search biocViews: MotifDiscovery, GeneRegulation Author: Adam Ameur Maintainer: Adam Ameur source.ver: src/contrib/BCRANK_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BCRANK_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BCRANK_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BCRANK_1.22.0.tgz vignettes: vignettes/BCRANK/inst/doc/BCRANK_intro_fig1.pdf, vignettes/BCRANK/inst/doc/BCRANK_intro_fig2.pdf, vignettes/BCRANK/inst/doc/BCRANK.pdf vignetteTitles: BCRANK_intro_fig1.pdf, BCRANK_intro_fig2.pdf, BCRANK hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BCRANK/inst/doc/BCRANK.R Package: beadarray Version: 2.10.0 Depends: R (>= 2.13.0), BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), methods, ggplot2 Imports: BeadDataPackR, limma, AnnotationDbi, stats4, BiocGenerics, reshape2 Suggests: lumi, vsn, affy, hwriter, beadarrayExampleData, illuminaHumanv3.db, gridExtra License: GPL-2 Archs: i386, x64 MD5sum: a37ed994e7c183408adb0dfcf4dbeb9c NeedsCompilation: yes Title: Quality assessment and low-level analysis for Illumina BeadArray data Description: The package is able to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided. biocViews: Microarray, OneChannel, QualityControl, Preprocessing Author: Mark Dunning, Mike Smith, Jonathan Cairns, Andy Lynch, Matt Ritchie Maintainer: Mark Dunning source.ver: src/contrib/beadarray_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/beadarray_2.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/beadarray_2.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/beadarray_2.10.0.tgz vignettes: vignettes/beadarray/inst/doc/beadarray.pdf, vignettes/beadarray/inst/doc/beadlevel.pdf, vignettes/beadarray/inst/doc/beadsummary.pdf, vignettes/beadarray/inst/doc/ImageProcessing.pdf vignetteTitles: beadarray.pdf, beadlevel.pdf, beadsummary.pdf, ImageProcessing.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/beadarray/inst/doc/beadarray.R, vignettes/beadarray/inst/doc/beadlevel.R, vignettes/beadarray/inst/doc/beadsummary.R, vignettes/beadarray/inst/doc/ImageProcessing.R importsMe: arrayQualityMetrics, epigenomix suggestsMe: beadarraySNP, lumi Package: beadarraySNP Version: 1.26.0 Depends: methods, Biobase (>= 2.5.5), quantsmooth Suggests: aCGH, affy, limma, snapCGH, beadarray, DNAcopy License: GPL-2 MD5sum: b237ccc868b0799ccd015bd5d557f671 NeedsCompilation: no Title: Normalization and reporting of Illumina SNP bead arrays Description: Importing data from Illumina SNP experiments and performing copy number calculations and reports. biocViews: CopyNumberVariants, SNP, GeneticVariability, TwoChannel, Preprocessing, DataImport Author: Jan Oosting Maintainer: Jan Oosting source.ver: src/contrib/beadarraySNP_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/beadarraySNP_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/beadarraySNP_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/beadarraySNP_1.26.0.tgz vignettes: vignettes/beadarraySNP/inst/doc/beadarraySNP.pdf vignetteTitles: beadarraySNP.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/beadarraySNP/inst/doc/beadarraySNP.R Package: BeadDataPackR Version: 1.12.0 License: GPL-2 Archs: i386, x64 MD5sum: 590fb83b55921c9679135643f3edf11c NeedsCompilation: yes Title: Compression of Illumina BeadArray data Description: Provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform biocViews: Microarray Author: Mike Smith, Andy Lynch Maintainer: Mike Smith source.ver: src/contrib/BeadDataPackR_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BeadDataPackR_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BeadDataPackR_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BeadDataPackR_1.12.0.tgz vignettes: vignettes/BeadDataPackR/inst/doc/BeadDataPackR.pdf vignetteTitles: BeadDataPackR.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BeadDataPackR/inst/doc/BeadDataPackR.R importsMe: beadarray Package: betr Version: 1.16.0 Depends: R(>= 2.6.0) Imports: Biobase (>= 2.5.5), limma, mvtnorm, methods, stats Suggests: Biobase License: LGPL MD5sum: ae7734e8588f67be0622c2fe5261fd07 NeedsCompilation: no Title: Identify differentially expressed genes in microarray time-course data Description: The betr package implements the BETR (Bayesian Estimation of Temporal Regulation) algorithm to identify differentially expressed genes in microarray time-course data. biocViews: Microarray, Bioinformatics, DifferentialExpression, TimeCourse Author: Martin Aryee Maintainer: Martin Aryee source.ver: src/contrib/betr_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/betr_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/betr_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/betr_1.16.0.tgz vignettes: vignettes/betr/inst/doc/betr.pdf vignetteTitles: BETR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/betr/inst/doc/betr.R Package: bgafun Version: 1.22.0 Depends: made4, seqinr,ade4 License: Artistic-2.0 MD5sum: adbea1f70d4d14136baa3a0f127e0e88 NeedsCompilation: no Title: BGAfun A method to identify specifity determining residues in protein families Description: A method to identify specifity determining residues in protein families using Between Group Analysis biocViews: Bioinformatics,Classification Author: Iain Wallace Maintainer: Iain Wallace source.ver: src/contrib/bgafun_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/bgafun_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/bgafun_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/bgafun_1.22.0.tgz vignettes: vignettes/bgafun/inst/doc/bgafun.pdf vignetteTitles: bgafun.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bgafun/inst/doc/bgafun.R Package: BGmix Version: 1.20.0 Depends: R (>= 2.3.1), KernSmooth License: GPL-2 MD5sum: d464b2e9bcacae03d30c1ccf314b9e2f NeedsCompilation: yes Title: Bayesian models for differential gene expression Description: Fully Bayesian mixture models for differential gene expression biocViews: Microarray, DifferentialExpression, MultipleComparisons Author: Alex Lewin, Natalia Bochkina Maintainer: Alex Lewin source.ver: src/contrib/BGmix_1.20.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/BGmix_1.20.0.tgz vignettes: vignettes/BGmix/inst/doc/BGmix.pdf vignetteTitles: BGmix Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BGmix/inst/doc/BGmix.R Package: bgx Version: 1.24.0 Depends: R (>= 2.0.1), Biobase, affy (>= 1.5.0), gcrma (>= 2.4.1) Suggests: affydata, hgu95av2cdf License: GPL-2 Archs: i386, x64 MD5sum: 3ca7cab3e47dd9f2303e845235b8ad30 NeedsCompilation: yes Title: Bayesian Gene eXpression Description: Bayesian integrated analysis of Affymetrix GeneChips biocViews: Microarray, DifferentialExpression Author: Ernest Turro, Graeme Ambler, Anne-Mette K Hein Maintainer: Ernest Turro source.ver: src/contrib/bgx_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/bgx_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/bgx_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/bgx_1.24.0.tgz vignettes: vignettes/bgx/inst/doc/bgx.pdf vignetteTitles: HowTo BGX hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bgx/inst/doc/bgx.R Package: BHC Version: 1.12.0 License: GPL-3 Archs: i386, x64 MD5sum: 60f3673b7d49e3236c08099965c12ef7 NeedsCompilation: yes Title: Bayesian Hierarchical Clustering Description: The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. This avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric. This implementation accepts multinomial (i.e. discrete, with 2+ categories) or time-series data. This version also includes a randomised algorithm which is more efficient for larger data sets. biocViews: Microarray, Clustering Author: Rich Savage, Emma Cooke, Robert Darkins, Yang Xu Maintainer: Rich Savage source.ver: src/contrib/BHC_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BHC_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BHC_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BHC_1.12.0.tgz vignettes: vignettes/BHC/inst/doc/bhc.pdf vignetteTitles: Bayesian Hierarchical Clustering hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BHC/inst/doc/bhc.R Package: BicARE Version: 1.18.0 Depends: R (>= 1.8.0), Biobase (>= 2.5.5), multtest, GSEABase License: GPL-2 Archs: i386, x64 MD5sum: 688a1bdb974862ecda83be5a2f4814b8 NeedsCompilation: yes Title: Biclustering Analysis and Results Exploration Description: Biclustering Analysis and Results Exploration biocViews: Microarray, Transcription, Bioinformatics, Clustering Author: Pierre Gestraud Maintainer: Pierre Gestraud URL: http://bioinfo.curie.fr source.ver: src/contrib/BicARE_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BicARE_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BicARE_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BicARE_1.18.0.tgz vignettes: vignettes/BicARE/inst/doc/BicARE.pdf vignetteTitles: BicARE hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BicARE/inst/doc/BicARE.R Package: bigmemoryExtras Version: 1.2.0 Depends: R (>= 2.12), bigmemory (>= 4.3) Imports: bigmemory, biganalytics, methods, Biobase Suggests: RUnit, BiocGenerics (>= 0.1.0) License: Artistic-2.0 OS_type: unix MD5sum: b567a301a457b9fb4c75b72bb7e04687 NeedsCompilation: no Title: An extension of the bigmemory package with added safety, convenience, and a factor class. Description: This package defines a "BigMatrix" ReferenceClass which adds safety and convenience features to the filebacked.big.matrix class from the bigmemory package. BigMatrix protects against segfaults by monitoring and gracefully restoring the connection to on-disk data and it also protects against accidental data modification with a filesystem-based permissions system. We provide utilities for using BigMatrix-derived classes as assayData matrices within the Biobase package's eSet family of classes. BigMatrix provides some optimizations related to attaching to, and indexing into, file-backed matrices with dimnames. Additionally, the package provides a "BigMatrixFactor" class, a file-backed matrix with factor properties. biocViews: Infrastructure, DataRepresentation Author: Peter M. Haverty Maintainer: Peter M. Haverty source.ver: src/contrib/bigmemoryExtras_1.2.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/bigmemoryExtras_1.2.0.tgz vignettes: vignettes/bigmemoryExtras/inst/doc/bigmemoryExtras.pdf vignetteTitles: bigmemoryExtras hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bigmemoryExtras/inst/doc/bigmemoryExtras.R importsMe: gCMAP, gCMAPWeb Package: Biobase Version: 2.20.1 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), utils Imports: methods, BiocGenerics Suggests: tools, tkWidgets, ALL, RUnit, golubEsets License: Artistic-2.0 Archs: i386, x64 MD5sum: 29f5c99953f934c97032f5c24ddffde9 NeedsCompilation: yes Title: Biobase: Base functions for Bioconductor Description: Functions that are needed by many other packages or which replace R functions. biocViews: Infrastructure, Bioinformatics Author: R. Gentleman, V. Carey, M. Morgan, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Biobase_2.20.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/Biobase_2.20.1.zip win64.binary.ver: bin/windows64/contrib/2.16/Biobase_2.20.1.zip mac.binary.ver: bin/macosx/contrib/2.16/Biobase_2.20.1.tgz vignettes: vignettes/Biobase/inst/doc/BiobaseDevelopment.pdf, vignettes/Biobase/inst/doc/Bioconductor.pdf, vignettes/Biobase/inst/doc/esApply.pdf, vignettes/Biobase/inst/doc/ExpressionSetIntroduction.pdf, vignettes/Biobase/inst/doc/HowTo.pdf, vignettes/Biobase/inst/doc/Qviews.pdf vignetteTitles: Notes for eSet developers, Bioconductor Overview, esApply Introduction, An introduction to Biobase and ExpressionSets, Notes for writing introductory 'how to' documents, quick views of eSet instances hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Biobase/inst/doc/BiobaseDevelopment.R, vignettes/Biobase/inst/doc/Bioconductor.R, vignettes/Biobase/inst/doc/esApply.R, vignettes/Biobase/inst/doc/ExpressionSetIntroduction.R, vignettes/Biobase/inst/doc/HowTo.R, vignettes/Biobase/inst/doc/Qviews.R dependsOnMe: a4Base, a4Core, ACME, affy, affycomp, affyContam, affycoretools, affyPLM, affyQCReport, AGDEX, Agi4x44PreProcess, altcdfenvs, annaffy, AnnotationDbi, AnnotationForge, ArrayExpress, arrayMvout, ArrayTools, beadarray, beadarraySNP, bgx, BicARE, BiocCaseStudies, BioMVCClass, BioNet, birta, BrainStars, CAMERA, cancerclass, casper, Category, categoryCompare, cellHTS, cellHTS2, CGHbase, CGHcall, CGHregions, charm, chimera, chroGPS, clippda, clusterStab, CMA, cn.farms, cn.mops, codelink, convert, copa, ddCt, DESeq, DESeq2, DEXSeq, DFP, DSS, dualKS, dyebias, easyRNASeq, EBarrays, EDASeq, eisa, epigenomix, ExiMiR, fabia, factDesign, fastseg, flowClust, flowCore, flowWorkspace, frma, gaga, GeneAnswers, GeneExpressionSignature, GeneMeta, geneRecommender, GeneRegionScan, GeneSelectMMD, GeneSelector, geNetClassifier, genoset, GEOquery, GOFunction, goProfiles, 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annotate, AnnotationDbi, AnnotationForge, annotationTools, ArrayExpressHTS, arrayQualityMetrics, ArrayTools, attract, betr, bigmemoryExtras, biocViews, BioSeqClass, BiSeq, BrainStars, bsseq, Category, categoryCompare, CGHnormaliter, charm, ChIPXpress, ChromHeatMap, clipper, ConsensusClusterPlus, crlmm, cycle, DESeq2, EBarrays, ecolitk, epigenomix, farms, ffpe, flowCore, flowFlowJo, flowFP, flowMeans, flowQB, flowStats, flowType, flowUtils, flowViz, flowWorkspace, frma, frmaTools, gCMAP, gCMAPWeb, gcrma, genefilter, GeneMeta, geneplotter, geneRecommender, GeneRegionScan, GeneSelectMMD, genomeIntervals, GenomicFeatures, GEOsubmission, GGBase, ggbio, GGtools, girafe, globaltest, gmapR, GOFunction, GOstats, GSEABase, GSRI, GSVA, Gviz, Harshlight, HEM, HiTC, hopach, HTqPCR, IdMappingAnalysis, iFlow, imageHTS, lapmix, LiquidAssociation, lumi, maanova, makecdfenv, maSigPro, mBPCR, MCRestimate, metaArray, methyAnalysis, methylumi, MiChip, MinimumDistance, MiPP, MmPalateMiRNA, multiscan, mzR, nucleR, oligoClasses, OrderedList, PADOG, PAnnBuilder, panp, pcaGoPromoter, PCpheno, piano, plateCore, plier, ppiStats, prada, PROMISE, puma, pvac, pvca, qpgraph, QuasR, R453Plus1Toolbox, randPack, ReadqPCR, RGalaxy, Rmagpie, rMAT, rols, rqubic, rSFFreader, Rtreemix, SAGx, ShortRead, simpleaffy, SLGI, SNPchip, spade, spkTools, splicegear, synapter, TEQC, tigre, timecourse, topGO, TSSi, twilight, VanillaICE, VariantAnnotation, virtualArray, XDE, xmapcore suggestsMe: annotate, betr, BiocCaseStudies, BiocGenerics, biocViews, BSgenome, Category, DART, farms, genefilter, genefu, geneplotter, GlobalAncova, globaltest, Heatplus, les, nem, OSAT, pkgDepTools, ROC, survcomp, tkWidgets, TypeInfo, vbmp, widgetTools Package: BiocCaseStudies Version: 1.22.0 Depends: tools, methods, utils, Biobase Suggests: affy (>= 1.17.3), affyPLM (>= 1.15.1), affyQCReport (>= 1.17.0), ALL (>= 1.4.3), annaffy (>= 1.11.1), annotate (>= 1.17.3), AnnotationDbi (>= 1.1.6), apComplex (>= 2.5.0), Biobase (>= 1.17.5), bioDist (>= 1.11.3), biocGraph (>= 1.1.1), biomaRt (>= 1.13.5), CCl4 (>= 1.0.6), CLL (>= 1.2.4), Category (>= 2.5.0), class (>= 7.2-38), cluster (>= 1.11.9), convert (>= 1.15.0), gcrma (>= 2.11.1), genefilter (>= 1.17.6), geneplotter (>= 1.17.2), GO.db (>= 2.0.2), GOstats (>= 2.5.0), graph (>= 1.17.4), GSEABase (>= 1.1.13), hgu133a.db (>= 2.0.2), hgu95av2.db, hgu95av2cdf (>= 2.0.0), hgu95av2probe (>= 2.0.0), hopach (>= 1.13.0), KEGG.db (>= 2.0.2), kohonen (>= 2.0.2), lattice (>= 0.17.2), latticeExtra (>= 0.3-1), limma (>= 2.13.1), MASS (>= 7.2-38), MLInterfaces (>= 1.13.17), multtest (>= 1.19.0), org.Hs.eg.db (>= 2.0.2), ppiStats (>= 1.5.4), randomForest (>= 4.5-20), RBGL (>= 1.15.6), RColorBrewer (>= 1.0-2), Rgraphviz (>= 1.17.11), vsn (>= 3.4.0), weaver (>= 1.5.0), xtable (>= 1.5-2), yeastExpData (>= 0.9.11) License: Artistic-2.0 MD5sum: e5f24c9e1f82687b1e1aa81f907904aa NeedsCompilation: no Title: BiocCaseStudies: Support for the Case Studies Monograph Description: Software and data to support the case studies. biocViews: Infrastructure, Bioinformatics Author: R. Gentleman, W. Huber, F. Hahne, M. Morgan, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocCaseStudies_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BiocCaseStudies_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BiocCaseStudies_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BiocCaseStudies_1.22.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: BiocGenerics Version: 0.6.0 Depends: methods, graphics, stats, parallel Imports: methods, graphics, stats, parallel Suggests: Biobase, IRanges, GenomicRanges, AnnotationDbi, oligoClasses, oligo, affyPLM, flowClust, RUnit License: Artistic-2.0 MD5sum: c4b4b3ede40a95345c08fc1dae6301dd NeedsCompilation: no Title: Generic functions for Bioconductor Description: S4 generic functions needed by many Bioconductor packages. biocViews: Infrastructure Author: The Bioconductor Dev Team Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocGenerics_0.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BiocGenerics_0.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BiocGenerics_0.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BiocGenerics_0.6.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affy, affyPLM, altcdfenvs, AnnotationDbi, AnnotationForge, beadarray, Biobase, Biostrings, BSgenome, bsseq, Category, categoryCompare, ChIPpeakAnno, chipseq, ChIPseqR, ChromHeatMap, cn.mops, codelink, copynumber, cummeRbund, dexus, easyRNASeq, EDASeq, ensemblVEP, flowQ, flowWorkspace, genomeIntervals, GenomicFeatures, GenomicRanges, Genominator, genoset, GSEABase, gwascat, htSeqTools, IRanges, KEGGSOAP, minfi, MinimumDistance, MotIV, MSnbase, nucleR, oligo, oligoClasses, PICS, PWMEnrich, R453Plus1Toolbox, REDseq, Repitools, rMAT, rsbml, ShortRead, simpleaffy, SplicingGraphs, TEQC, tigre, TSSi, VariantAnnotation, virtualArray, xcms importsMe: affy, affyPLM, annmap, annotate, AnnotationDbi, AnnotationForge, AnnotationHub, beadarray, Biobase, biocGraph, Biostrings, biovizBase, BiSeq, Category, categoryCompare, cghMCR, ChemmineR, ChIPpeakAnno, chipseq, ChromHeatMap, cn.farms, cn.mops, codelink, crlmm, cummeRbund, DrugVsDisease, EDASeq, eiR, eisa, epigenomix, fastseg, ffpe, flowClust, flowCore, flowFP, flowMerge, flowQ, flowStats, frma, gCMAP, gCMAPWeb, geNetClassifier, GenomicFeatures, GenomicRanges, GGBase, ggbio, GGtools, graph, GSEABase, GSVA, Gviz, HTSeqGenie, IRanges, KCsmart, LVSmiRNA, methylumi, minfi, MinimumDistance, MiRaGE, MotifDb, MotIV, nucleR, oligo, oligoClasses, OrganismDbi, pcaMethods, PING, plrs, prada, pRoloc, QuasR, R453Plus1Toolbox, RCytoscape, REDseq, Repitools, RGalaxy, Ringo, rMAT, Rsamtools, rsbml, rtracklayer, ShortRead, simpleaffy, SLGI, snpStats, SplicingGraphs, Streamer, tigre, triform, TSSi, UniProt.ws, VariantAnnotation, VariantTools, XDE suggestsMe: bigmemoryExtras, BiocInstaller, BiocParallel, bumphunter, CAMERA, CellNOptR, ChIPpeakAnno, ChIPXpress, clipper, CNORfeeder, CNORfuzzy, DBChIP, ensemblVEP, GENE.E, GeneNetworkBuilder, GOstats, GraphPAC, GWASTools, illuminaio, inSilicoMerging, KEGGREST, motifStack, PathNet, pathview, rBiopaxParser, Rcade, Rgraphviz, ROntoTools, SANTA Package: biocGraph Version: 1.22.0 Depends: Rgraphviz, graph Imports: Rgraphviz, geneplotter, graph, BiocGenerics, methods Suggests: fibroEset, geneplotter, hgu95av2.db License: Artistic-2.0 MD5sum: 38a01e399168d918730381f5f762acee NeedsCompilation: no Title: Graph examples and use cases in Bioinformatics Description: This package provides examples and code that make use of the different graph related packages produced by Bioconductor. biocViews: NetworkVisualization, GraphsAndNetworks Author: Li Long , Robert Gentleman , Seth Falcon Florian Hahne Maintainer: Florian Hahne source.ver: src/contrib/biocGraph_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/biocGraph_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/biocGraph_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/biocGraph_1.22.0.tgz vignettes: vignettes/biocGraph/inst/doc/biocGraph.pdf, vignettes/biocGraph/inst/doc/layingOutPathways.pdf vignetteTitles: Examples of plotting graphs Using Rgraphviz, HOWTO layout pathways hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biocGraph/inst/doc/biocGraph.R, vignettes/biocGraph/inst/doc/layingOutPathways.R suggestsMe: BiocCaseStudies Package: BiocInstaller Version: 1.10.4 Depends: R (>= 2.16.0) Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: d005eee670ee1e5beadcacd568870223 NeedsCompilation: no Title: Install/Update Bioconductor and CRAN Packages Description: Installs/updates Bioconductor and CRAN packages biocViews: Software Author: Dan Tenenbaum and Biocore Team Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocInstaller_1.10.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/BiocInstaller_1.10.4.zip win64.binary.ver: bin/windows64/contrib/2.16/BiocInstaller_1.10.4.zip mac.binary.ver: bin/macosx/contrib/2.16/BiocInstaller_1.10.4.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affylmGUI importsMe: affy, AnnotationHub, gcrma, oligoClasses, QuasR, webbioc suggestsMe: GOSemSim, pkgDepTools Package: BiocParallel Version: 0.2.0 Imports: methods, parallel, foreach, tools Suggests: BiocGenerics, doParallel License: GPL-2 | GPL-3 MD5sum: 96829ccfb57ccefa016f2c1e763553c4 NeedsCompilation: no Title: Bioconductor facilities for parallel evaluation Description: This package provides modified versions and novel implementation of functions for parallel evaluation, tailored to use with Bioconductor objects. biocViews: HighThroughputSequencing, Infrastructure Author: Martin Morgan Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocParallel_0.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BiocParallel_0.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BiocParallel_0.2.0.zip hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: biocViews Version: 1.28.0 Depends: R (>= 2.4.0) Imports: Biobase, graph (>= 1.9.26), methods, RBGL (>= 1.13.5), tools, utils, XML, RCurl, RUnit, knitr Suggests: Biobase License: Artistic-2.0 MD5sum: 47ff1c86f0a73840982958c8247eb29d NeedsCompilation: no Title: Categorized views of R package repositories Description: structures for vocabularies and narratives of views biocViews: Infrastructure Author: VJ Carey , BJ Harshfield , S Falcon Maintainer: Bioconductor Package Maintainer URL: http://www.bioconductor.org/packages/release/BiocViews.html source.ver: src/contrib/biocViews_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/biocViews_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/biocViews_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/biocViews_1.28.0.tgz vignettes: vignettes/biocViews/inst/doc/createReposHtml.pdf, vignettes/biocViews/inst/doc/HOWTO-BCV.pdf vignetteTitles: biocViews-CreateRepositoryHTML, biocViews-HOWTO hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biocViews/inst/doc/createReposHtml.R, vignettes/biocViews/inst/doc/HOWTO-BCV.R dependsOnMe: Risa Package: bioDist Version: 1.32.0 Depends: R (>= 2.0), methods, Biobase,KernSmooth Suggests: locfit License: Artistic-2.0 MD5sum: eae9424efd6a3b2fb13a1757ad837168 NeedsCompilation: no Title: Different distance measures Description: A collection of software tools for calculating distance measures. biocViews: Bioinformatics Author: B. Ding, R. Gentleman and Vincent Carey Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/bioDist_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/bioDist_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/bioDist_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/bioDist_1.32.0.tgz vignettes: vignettes/bioDist/inst/doc/bioDist.pdf vignetteTitles: bioDist Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bioDist/inst/doc/bioDist.R dependsOnMe: flowQ suggestsMe: BiocCaseStudies Package: biomaRt Version: 2.16.0 Depends: methods Imports: utils, XML, RCurl Suggests: annotate License: Artistic-2.0 MD5sum: 57b1ca38d53380bd15259a9d4e5bd37b NeedsCompilation: no Title: Interface to BioMart databases (e.g. Ensembl, COSMIC ,Wormbase and Gramene) Description: In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (http://www.biomart.org). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining. biocViews: Annotation Author: Steffen Durinck , Wolfgang Huber Maintainer: Steffen Durinck source.ver: src/contrib/biomaRt_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/biomaRt_2.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/biomaRt_2.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/biomaRt_2.16.0.tgz vignettes: vignettes/biomaRt/inst/doc/biomaRt.pdf vignetteTitles: The biomaRt users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biomaRt/inst/doc/biomaRt.R dependsOnMe: ChIPpeakAnno, domainsignatures, DrugVsDisease, easyRNASeq, genefu, GenomeGraphs, MineICA, SeqGSEA, VegaMC importsMe: affycoretools, ArrayExpressHTS, ChIPpeakAnno, DEXSeq, GenomicFeatures, Gviz, HTSanalyzeR, IdMappingRetrieval, MEDIPS, methyAnalysis, phenoTest, R453Plus1Toolbox, RNAither suggestsMe: BiocCaseStudies, GeneAnswers, GenomicFeatures, Genominator, Gviz, isobar, maDB, MineICA, MiRaGE, oneChannelGUI, piano, Rcade, RIPSeeker, rTANDEM, ShortRead, SIM Package: BioMVCClass Version: 1.28.0 Depends: R (>= 2.1.0), methods, MVCClass, Biobase, graph, Rgraphviz License: LGPL MD5sum: 66442a6e1152e4d596fe95846ead76de NeedsCompilation: no Title: Model-View-Controller (MVC) Classes That Use Biobase Description: Creates classes used in model-view-controller (MVC) design biocViews: Visualization, Infrastructure, GraphsAndNetworks Author: Elizabeth Whalen Maintainer: Elizabeth Whalen source.ver: src/contrib/BioMVCClass_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BioMVCClass_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BioMVCClass_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BioMVCClass_1.28.0.tgz vignettes: vignettes/BioMVCClass/inst/doc/BioMVCClass.pdf vignetteTitles: BioMVCClass hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioMVCClass/inst/doc/BioMVCClass.R Package: biomvRCNS Version: 1.0.6 Depends: IRanges, GenomicRanges, Gviz Imports: methods, mvtnorm Suggests: cluster, parallel, GenomicFeatures, dynamicTreeCut, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene License: GPL (>= 2) Archs: i386, x64 MD5sum: 089b46037c34a1a59c22bffffe57ccc3 NeedsCompilation: yes Title: Copy Number study and Segmentation for multivariate biological data Description: In this package, a Hidden Semi Markov Model (HSMM) and one homogeneous segmentation model are designed and implemented for segmentation genomic data, with the aim of assisting in transcripts detection using high throughput technology like RNA-seq or tiling array, and copy number analysis using aCGH or sequencing. biocViews: aCGH, CopyNumberVariants, Microarray, HighThroughputSequencing, Sequencing, Visualization, Genetics Author: Yang Du Maintainer: Yang Du source.ver: src/contrib/biomvRCNS_1.0.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/biomvRCNS_1.0.6.zip win64.binary.ver: bin/windows64/contrib/2.16/biomvRCNS_1.0.6.zip mac.binary.ver: bin/macosx/contrib/2.16/biomvRCNS_1.0.6.tgz vignettes: vignettes/biomvRCNS/inst/doc/biomvRCNS.pdf vignetteTitles: biomvRCNS package introduction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biomvRCNS/inst/doc/biomvRCNS.R Package: BioNet Version: 1.18.0 Depends: R (>= 2.10.0), Biobase, graph, RBGL Imports: igraph0, AnnotationDbi Suggests: rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML License: GPL (>= 2) MD5sum: 827847ca0d09a71ccd4a5bcb2b7cbae5 NeedsCompilation: no Title: Routines for the functional analysis of biological networks Description: This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork. biocViews: Microarray, DataImport, GraphsAndNetworks, NetworkAnalysis, NetworkEnrichment, GeneExpression, DifferentialExpression Author: Marcus Dittrich and Daniela Beisser Maintainer: Marcus Dittrich URL: http://bionet.bioapps.biozentrum.uni-wuerzburg.de/ source.ver: src/contrib/BioNet_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BioNet_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BioNet_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BioNet_1.18.0.tgz vignettes: vignettes/BioNet/inst/doc/bum1.pdf, vignettes/BioNet/inst/doc/bum2.pdf, vignettes/BioNet/inst/doc/cytoscape.pdf, vignettes/BioNet/inst/doc/prec_recall_large.pdf, vignettes/BioNet/inst/doc/prec_recall_small.pdf, vignettes/BioNet/inst/doc/Tutorial-3dplot.pdf, vignettes/BioNet/inst/doc/Tutorial.pdf vignetteTitles: bum1.pdf, bum2.pdf, cytoscape.pdf, prec_recall_large.pdf, prec_recall_small.pdf, Tutorial-3dplot.pdf, BioNet Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioNet/inst/doc/Tutorial.R importsMe: HTSanalyzeR Package: BioSeqClass Version: 1.18.0 Depends: R (>= 2.10), scatterplot3d Imports: Biostrings, ipred, e1071, klaR, randomForest, class, tree, nnet, rpart, party, foreign, Biobase, utils, stats, grDevices Suggests: scatterplot3d License: LGPL (>= 2.0) MD5sum: 04b5036877e6571211b8aeddab2c084b NeedsCompilation: no Title: Classification for Biological Sequences Description: Extracting Features from Biological Sequences and Building Classification Model biocViews: Classification Author: Li Hong sysptm@gmail.com Maintainer: Li Hong source.ver: src/contrib/BioSeqClass_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BioSeqClass_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BioSeqClass_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BioSeqClass_1.18.0.tgz vignettes: vignettes/BioSeqClass/inst/doc/BioSeqClass.pdf, vignettes/BioSeqClass/inst/doc/cvFFSClassify0005.pdf, vignettes/BioSeqClass/inst/doc/FeatureSets16.pdf, vignettes/BioSeqClass/inst/doc/workflow.pdf vignetteTitles: Using the BioSeqClass Package, cvFFSClassify0005.pdf, FeatureSets16.pdf, workflow.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioSeqClass/inst/doc/BioSeqClass.R Package: Biostrings Version: 2.28.0 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.5.4), IRanges (>= 1.17.41) Imports: graphics, methods, stats, utils, BiocGenerics, IRanges LinkingTo: IRanges Suggests: BSgenome (>= 1.13.14), BSgenome.Celegans.UCSC.ce2 (>= 1.3.11), BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.11), BSgenome.Hsapiens.UCSC.hg18, drosophila2probe, hgu95av2probe, hgu133aprobe, GenomicFeatures (>= 1.3.14), hgu95av2cdf, affy, affydata (>= 1.11.5), RUnit Enhances: Rmpi License: Artistic-2.0 Archs: i386, x64 MD5sum: 71fcf7fc88334584b66d19a0d254293b NeedsCompilation: yes Title: String objects representing biological sequences, and matching algorithms Description: Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences. biocViews: SequenceMatching, Genetics, Sequencing, Infrastructure, DataImport, DataRepresentation Author: H. Pages, P. Aboyoun, R. Gentleman, and S. DebRoy Maintainer: H. Pages source.ver: src/contrib/Biostrings_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Biostrings_2.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Biostrings_2.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Biostrings_2.28.0.tgz vignettes: vignettes/Biostrings/inst/doc/Biostrings2Classes.pdf, vignettes/Biostrings/inst/doc/BiostringsQuickOverview.pdf, vignettes/Biostrings/inst/doc/matchprobes.pdf, vignettes/Biostrings/inst/doc/MultipleAlignments.pdf, vignettes/Biostrings/inst/doc/PairwiseAlignments.pdf vignetteTitles: A short presentation of the basic classes defined in Biostrings 2, Biostrings Quick Overview, Handling probe sequence information, Multiple Alignments, Pairwise Sequence Alignments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Biostrings/inst/doc/Biostrings2Classes.R, vignettes/Biostrings/inst/doc/BiostringsQuickOverview.R, vignettes/Biostrings/inst/doc/matchprobes.R, vignettes/Biostrings/inst/doc/MultipleAlignments.R, vignettes/Biostrings/inst/doc/PairwiseAlignments.R dependsOnMe: altcdfenvs, BRAIN, BSgenome, ChIPpeakAnno, ChIPsim, CorMut, DASiR, DECIPHER, deepSNV, easyRNASeq, GeneRegionScan, genomes, iPAC, minfi, MotifDb, oneChannelGUI, qrqc, R453Plus1Toolbox, REDseq, rGADEM, Rsamtools, rSFFreader, RSVSim, SCAN.UPC, seqbias, ShortRead, triplex, waveTiling importsMe: AffyCompatible, ArrayExpressHTS, BCRANK, BioSeqClass, biovizBase, charm, ChIPpeakAnno, ChIPseqR, ChIPsim, DECIPHER, ensemblVEP, gcrma, GeneRegionScan, GenomicFeatures, girafe, gmapR, Gviz, gwascat, HiTC, HTSeqGenie, KEGGREST, MEDIPS, MEDME, methVisual, microRNA, motifRG, MotIV, oligo, oligoClasses, OTUbase, pdInfoBuilder, phyloseq, qrqc, QuasR, R453Plus1Toolbox, REDseq, rGADEM, Rolexa, Rsamtools, rSFFreader, rtracklayer, ShortRead, triplex, VariantAnnotation, VariantTools suggestsMe: annotate, CSAR, exomeCopy, GenomicFeatures, GenomicRanges, methylumi, microRNA, MiRaGE, pcaGoPromoter, procoil Package: biovizBase Version: 1.8.1 Depends: R (>= 2.10), methods Imports: methods, grDevices, stats, scales, Hmisc, RColorBrewer, dichromat, BiocGenerics, IRanges, GenomicRanges, Biostrings, Rsamtools, GenomicFeatures Suggests: BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, BSgenome, rtracklayer License: Artistic-2.0 Archs: i386, x64 MD5sum: 6c1285c05ba5bb7623dd0e0fec3de086 NeedsCompilation: yes Title: Basic graphic utilities for visualization of genomic data. Description: The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and encourages consistency. biocViews: Infrastructure, Visualization, Bioinformatics, Preprocessing Author: Tengfei Yin, Michael Lawrence, Dianne Cook Maintainer: Tengfei Yin source.ver: src/contrib/biovizBase_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/biovizBase_1.8.1.zip win64.binary.ver: bin/windows64/contrib/2.16/biovizBase_1.8.1.zip mac.binary.ver: bin/macosx/contrib/2.16/biovizBase_1.8.1.tgz vignettes: vignettes/biovizBase/inst/doc/intro.pdf, vignettes/biovizBase/inst/doc/intro-shrinkageFun.pdf, vignettes/biovizBase/inst/doc/intro-shrink-single.pdf vignetteTitles: An Introduction to biovizBase, intro-shrinkageFun.pdf, intro-shrink-single.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biovizBase/inst/doc/intro.R dependsOnMe: qrqc importsMe: Gviz, qrqc Package: birta Version: 1.4.0 Depends: limma, MASS, R(>= 2.10), Biobase, methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 30a601c01d2b873b68eb9c6e92ca75ea NeedsCompilation: yes Title: Bayesian Inference of Regulation of Transcriptional Activity Description: Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. birta (Bayesian Inference of Regulation of Transcriptional Activity) uses the regulatory networks of TFs and miRNAs together with mRNA and miRNA expression data to predict switches in regulatory activity between two conditions. A Bayesian network is used to model the regulatory structure and Markov-Chain-Monte-Carlo is applied to sample the activity states. biocViews: Microarray, Sequencing, GeneExpression, Transcription, Bioinformatics, GraphsAndNetworks Author: Benedikt Zacher, Khalid Abnaof, Stephan Gade, Erfan Younesi, Achim Tresch, Holger Froehlich Maintainer: Benedikt Zacher , Holger Froehlich source.ver: src/contrib/birta_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/birta_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/birta_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/birta_1.4.0.tgz vignettes: vignettes/birta/inst/doc/birta.pdf vignetteTitles: Bayesian Inference of Regulation of Transcriptional Activity hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/birta/inst/doc/birta.R Package: BiSeq Version: 1.0.3 Depends: R (>= 2.15.2), methods, IRanges (>= 1.17.24), GenomicRanges, Formula Imports: methods, BiocGenerics, Biobase, IRanges, GenomicRanges, rtracklayer, parallel, betareg, lokern, Formula License: LGPL-3 MD5sum: d680ad3547b9e1e26e709fcb9bfe7bf4 NeedsCompilation: no Title: Processing and analyzing bisulfite sequencing data Description: The BiSeq package provides useful classes and functions to handle and analyze targeted bisulfite sequencing (BS) data such as reduced-representation bisulfite sequencing (RRBS) data. In particular, it implements an algorithm to detect differentially methylated regions (DMRs). The package takes already aligned BS data from one or multiple samples. biocViews: Genetics, Sequencing, HighThroughputSequencing, Methylseq, DNAMethylation Author: Katja Hebestreit, Hans-Ulrich Klein Maintainer: Katja Hebestreit source.ver: src/contrib/BiSeq_1.0.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/BiSeq_1.0.3.zip win64.binary.ver: bin/windows64/contrib/2.16/BiSeq_1.0.3.zip mac.binary.ver: bin/macosx/contrib/2.16/BiSeq_1.0.3.tgz vignettes: vignettes/BiSeq/inst/doc/BiSeq.pdf vignetteTitles: An Introduction to BiSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BiSeq/inst/doc/BiSeq.R Package: BitSeq Version: 1.4.3 Depends: Rsamtools, zlibbioc Imports: IRanges LinkingTo: Rsamtools, zlibbioc Suggests: edgeR, DESeq License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: 94834584a36d29fdb224879a21a8ef6e NeedsCompilation: yes Title: Transcript expression inference and differential expression analysis for RNA-seq data Description: The BitSeq package is targeted for transcript expression analysis and differential expression analysis of RNA-seq data in two stage process. In the first stage it uses Bayesian inference methodology to infer expression of individual transcripts from individual RNA-seq experiments. The second stage of BitSeq embraces the differential expression analysis of transcript expression. Providing expression estimates from replicates of multiple conditions, Log-Normal model of the estimates is used for inferring the condition mean transcript expression and ranking the transcripts based on the likelihood of differential expression. biocViews: GeneExpression, DifferentialExpression, HighThroughputSequencing, RNAseq Author: Peter Glaus, Antti Honkela and Magnus Rattray Maintainer: Peter Glaus source.ver: src/contrib/BitSeq_1.4.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/BitSeq_1.4.3.zip win64.binary.ver: bin/windows64/contrib/2.16/BitSeq_1.4.3.zip mac.binary.ver: bin/macosx/contrib/2.16/BitSeq_1.4.3.tgz vignettes: vignettes/BitSeq/inst/doc/BitSeq.pdf vignetteTitles: BitSeq User Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/BitSeq/inst/doc/BitSeq.R Package: BRAIN Version: 1.6.6 Depends: R (>= 2.8.1), PolynomF, Biostrings, lattice License: GPL-2 MD5sum: b2b7c41320a218e8794e34751fe2b9e9 NeedsCompilation: no Title: Baffling Recursive Algorithm for Isotope distributioN calculations Description: Package for calculating aggregated isotopic distribution and exact center-masses for chemical substances (in this version composed of C, H, N, O and S). This is an implementation of the BRAIN algorithm described in the paper by J. Claesen, P. Dittwald, T. Burzykowski and D. Valkenborg. biocViews: Bioinformatics, MassSpectrometry, Proteomics Author: Piotr Dittwald, with contributions of Dirk Valkenborg and Jurgen Claesen Maintainer: Piotr Dittwald source.ver: src/contrib/BRAIN_1.6.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/BRAIN_1.6.6.zip win64.binary.ver: bin/windows64/contrib/2.16/BRAIN_1.6.6.zip mac.binary.ver: bin/macosx/contrib/2.16/BRAIN_1.6.6.tgz vignettes: vignettes/BRAIN/inst/doc/BRAIN-vignette.pdf vignetteTitles: BRAIN Usage hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BRAIN/inst/doc/BRAIN-vignette.R Package: BrainStars Version: 1.4.0 Depends: RCurl, Biobase, methods Imports: RJSONIO, Biobase License: Artistic-2.0 MD5sum: 3608f89af784e9f1f34d9994403c6724 NeedsCompilation: no Title: query gene expression data and plots from BrainStars (B*) Description: This package can search and get gene expression data and plots from BrainStars (B*). BrainStars is a quantitative expression database of the adult mouse brain. The database has genome-wide expression profile at 51 adult mouse CNS regions. biocViews: Microarray, OneChannel, DataImport Author: Itoshi NIKAIDO Maintainer: Itoshi NIKAIDO source.ver: src/contrib/BrainStars_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BrainStars_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BrainStars_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BrainStars_1.4.0.tgz vignettes: vignettes/BrainStars/inst/doc/BrainStars.pdf vignetteTitles: BrainStars hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BrainStars/inst/doc/BrainStars.R Package: bridge Version: 1.24.0 Depends: R (>= 1.9.0), rama License: GPL (>= 2) Archs: i386, x64 MD5sum: 8f9fcacd00d60a1299a4fa6737c38aa1 NeedsCompilation: yes Title: Bayesian Robust Inference for Differential Gene Expression Description: Test for differentially expressed genes with microarray data. This package can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a $t$-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space. biocViews: Microarray,OneChannel,TwoChannel,DifferentialExpression Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/bridge_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/bridge_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/bridge_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/bridge_1.24.0.tgz vignettes: vignettes/bridge/inst/doc/bridge.pdf vignetteTitles: bridge Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bridge/inst/doc/bridge.R Package: BSgenome Version: 1.28.0 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.1.2), IRanges (>= 1.13.6), GenomicRanges (>= 1.11.46), Biostrings (>= 2.23.3) Suggests: RUnit, BSgenome.Celegans.UCSC.ce2 (>= 1.3.11), BSgenome.Hsapiens.UCSC.hg19 (>= 1.3.11), SNPlocs.Hsapiens.dbSNP.20100427, hgu95av2probe, Biobase License: Artistic-2.0 MD5sum: d1f843788089890ee9cf3c74150c1949 NeedsCompilation: no Title: Infrastructure for Biostrings-based genome data packages Description: Infrastructure shared by all the Biostrings-based genome data packages biocViews: Genetics, Infrastructure, DataRepresentation, SequenceMatching, Annotation, SNP Author: Herve Pages Maintainer: H. Pages source.ver: src/contrib/BSgenome_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BSgenome_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BSgenome_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BSgenome_1.28.0.tgz vignettes: vignettes/BSgenome/inst/doc/BSgenomeForge.pdf, vignettes/BSgenome/inst/doc/GenomeSearching.pdf vignetteTitles: How to forge a BSgenome data package, Efficient genome searching with Biostrings and the BSgenome data packages hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BSgenome/inst/doc/BSgenomeForge.R, vignettes/BSgenome/inst/doc/GenomeSearching.R dependsOnMe: CAGEr, ChIPpeakAnno, chipseq, easyRNASeq, htSeqTools, MEDIPS, REDseq, rGADEM importsMe: charm, ChIPpeakAnno, chipseq, ggbio, girafe, gmapR, Gviz, MEDIPS, MethylSeekR, PING, QuasR, R453Plus1Toolbox, Repitools, rtracklayer, VariantAnnotation suggestsMe: Biostrings, biovizBase, GeneRegionScan, GenomicFeatures, GenomicRanges, MEDIPS, MiRaGE, oneChannelGUI, Repitools, waveTiling Package: bsseq Version: 0.8.0 Depends: R (>= 2.15), methods, BiocGenerics, IRanges, GenomicRanges, parallel, matrixStats Imports: scales, stats, graphics, Biobase, locfit Suggests: RUnit, bsseqData License: Artistic-2.0 MD5sum: cd115f69bedc336a3c83f6820ecc7789 NeedsCompilation: no Title: Analyze, manage and store bisulfite sequencing data Description: Tools for analyzing and visualizing bisulfite sequencing data biocViews: DNAMethylation Author: Kasper Daniel Hansen Maintainer: Kasper Daniel Hansen source.ver: src/contrib/bsseq_0.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/bsseq_0.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/bsseq_0.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/bsseq_0.8.0.tgz vignettes: vignettes/bsseq/inst/doc/bsseq_analysis.pdf, vignettes/bsseq/inst/doc/bsseq.pdf vignetteTitles: Analyzing WGBS with bsseq, The bsseq user's guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bsseq/inst/doc/bsseq_analysis.R, vignettes/bsseq/inst/doc/bsseq.R Package: BufferedMatrix Version: 1.24.0 Depends: R (>= 2.6.0), methods License: LGPL (>= 2) Archs: i386, x64 MD5sum: 25e3263483e076ded14c9b095038f2ef NeedsCompilation: yes Title: A matrix data storage object held in temporary files Description: A tabular style data object where most data is stored outside main memory. A buffer is used to speed up access to data. biocViews: Infrastructure Author: Benjamin Milo Bolstad Maintainer: Benjamin Milo Bolstad source.ver: src/contrib/BufferedMatrix_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BufferedMatrix_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BufferedMatrix_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BufferedMatrix_1.24.0.tgz vignettes: vignettes/BufferedMatrix/inst/doc/BufferedMatrix.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture1.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture2.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture3.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture4.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture5.pdf vignetteTitles: BufferedMatrix: Introduction, BufferedMatrixPicture1.pdf, BufferedMatrixPicture2.pdf, BufferedMatrixPicture3.pdf, BufferedMatrixPicture4.pdf, BufferedMatrixPicture5.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BufferedMatrix/inst/doc/BufferedMatrix.R dependsOnMe: BufferedMatrixMethods Package: BufferedMatrixMethods Version: 1.24.0 Depends: R (>= 2.6.0), BufferedMatrix (>= 1.3.0), methods LinkingTo: BufferedMatrix Suggests: affyio, affy License: GPL (>= 2) Archs: i386, x64 MD5sum: db9b393239773cfc89ed6186fd8b5788 NeedsCompilation: yes Title: Microarray Data related methods that utlize BufferedMatrix objects Description: Microarray analysis methods that use BufferedMatrix objects biocViews: Infrastructure Author: B. M. Bolstad Maintainer: B. M. Bolstad URL: http://www.bmbolstad.com source.ver: src/contrib/BufferedMatrixMethods_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BufferedMatrixMethods_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BufferedMatrixMethods_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BufferedMatrixMethods_1.24.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: bumphunter Version: 1.0.2 Depends: R (>= 2.10), IRanges, GenomicRanges, foreach, iterators, methods, parallel Imports: matrixStats, limma, itertools, doRNG Suggests: limma, RUnit, BiocGenerics, doParallel, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene License: Artistic-2.0 MD5sum: f0d5e53460d10efdd18d444d308547c5 NeedsCompilation: no Title: Bump Hunter Description: Tools for finding bumps in genomic data biocViews: DNAMethylation, Epigenetics, Infrastructure, MultipleComparisons Author: Rafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen, Harris A. Jaffee Maintainer: Rafael A. Irizarry source.ver: src/contrib/bumphunter_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/bumphunter_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/bumphunter_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/bumphunter_1.0.2.tgz vignettes: vignettes/bumphunter/inst/doc/bumphunter.pdf vignetteTitles: The bumphunter user's guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bumphunter/inst/doc/bumphunter.R Package: BUS Version: 1.16.0 Depends: R (>= 2.3.0), minet Imports: stats License: GPL-3 Archs: i386, x64 MD5sum: 2463c80df57025a5a0c39bbaa837136e NeedsCompilation: yes Title: Gene network reconstruction Description: This package can be used to compute associations among genes (gene-networks) or between genes and some external traits (i.e. clinical). biocViews: Preprocessing Author: Yin Jin, Hesen Peng, Lei Wang, Raffaele Fronza, Yuanhua Liu and Christine Nardini Maintainer: Yuanhua Liu source.ver: src/contrib/BUS_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/BUS_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/BUS_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/BUS_1.16.0.tgz vignettes: vignettes/BUS/inst/doc/bus.pdf vignetteTitles: bus.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BUS/inst/doc/bus.R Package: CAGEr Version: 1.2.9 Depends: methods, R (>= 2.15.0), BSgenome, BSgenome.Mmusculus.UCSC.mm9 Imports: Rsamtools, GenomicRanges, IRanges, data.table, beanplot, rtracklayer, som, VGAM Suggests: BSgenome.Drerio.UCSC.danRer7, BSgenome.Hsapiens.UCSC.hg18, FANTOM3and4CAGE Enhances: parallel License: GPL-3 MD5sum: 4aba626d920b713f63f905eb5c8f37c8 NeedsCompilation: no Title: Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining Description: Preprocessing of CAGE sequencing data, identification and normalization of transcription start sites and downstream analysis of transcription start sites clusters (promoters). biocViews: Preprocessing, Sequencing, HighThroughputSequencing, Transcription, Clustering, Visualization Author: Vanja Haberle, Department of Biology, University of Bergen, Norway Maintainer: Vanja Haberle source.ver: src/contrib/CAGEr_1.2.9.tar.gz win.binary.ver: bin/windows/contrib/2.16/CAGEr_1.2.9.zip win64.binary.ver: bin/windows64/contrib/2.16/CAGEr_1.2.9.zip mac.binary.ver: bin/macosx/contrib/2.16/CAGEr_1.2.9.tgz vignettes: vignettes/CAGEr/inst/doc/CAGEr.pdf vignetteTitles: CAGEr hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CAGEr/inst/doc/CAGEr.R Package: CALIB Version: 1.26.0 Depends: R (>= 2.10), limma, methods Imports: limma, methods, graphics, stats, utils License: LGPL Archs: i386, x64 MD5sum: 67ed68c27f359a96851a76caf250e0bb NeedsCompilation: yes Title: Calibration model for estimating absolute expression levels from microarray data Description: This package contains functions for normalizing spotted microarray data, based on a physically motivated calibration model. The model parameters and error distributions are estimated from external control spikes. biocViews: Microarray,TwoChannel,Preprocessing Author: Hui Zhao, Kristof Engelen, Bart De Moor and Kathleen Marchal Maintainer: Hui Zhao source.ver: src/contrib/CALIB_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CALIB_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CALIB_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CALIB_1.26.0.tgz vignettes: vignettes/CALIB/inst/doc/quickstart.pdf, vignettes/CALIB/inst/doc/readme.pdf vignetteTitles: CALIB Overview, readme.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CALIB/inst/doc/quickstart.R Package: CAMERA Version: 1.16.0 Depends: R (>= 2.1.0), methods, Biobase, xcms (>= 1.13.5), igraph Imports: methods, xcms, RBGL, graph, graphics, grDevices, stats, utils, Hmisc, igraph Suggests: faahKO, RUnit, BiocGenerics Enhances: Rmpi, snow License: GPL (>= 2) Archs: i386, x64 MD5sum: 7146693b6989884a6ca37939a6568b78 NeedsCompilation: yes Title: Collection of annotation related methods for mass spectrometry data Description: Annotation of peaklists generated by xcms, rule based annotation of isotopes and adducts, EIC correlation based tagging of unknown adducts and fragments biocViews: MassSpectrometry Author: Carsten Kuhl, Ralf Tautenhahn, Steffen Neumann {ckuhl|sneumann}@ipb-halle.de, rtautenh@scripps.edu Maintainer: Carsten Kuhl URL: http://msbi.ipb-halle.de/msbi/CAMERA/ source.ver: src/contrib/CAMERA_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CAMERA_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CAMERA_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CAMERA_1.16.0.tgz vignettes: vignettes/CAMERA/inst/doc/CAMERA.pdf vignetteTitles: Molecule Identification with CAMERA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CAMERA/inst/doc/CAMERA.R Package: cancerclass Version: 1.4.0 Depends: R (>= 2.10.1), Biobase, binom, methods, stats Suggests: cancerdata License: GPL-3 Archs: i386, x64 MD5sum: 7b3897afdc82a76648723b822dbaaa93 NeedsCompilation: yes Title: Development and validation of diagnostic tests from high-dimensional molecular data Description: The classification protocol starts with a feature selection step and continues with nearest-centroid classification. The accurarcy of the predictor can be evaluated using training and test set validation, leave-one-out cross-validation or in a multiple random validation protocol. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements. biocViews: Cancer, Microarray, Classification, Visualization Author: Jan Budczies, Daniel Kosztyla Maintainer: Daniel Kosztyla source.ver: src/contrib/cancerclass_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cancerclass_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cancerclass_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cancerclass_1.4.0.tgz vignettes: vignettes/cancerclass/inst/doc/vignette_cancerclass.pdf vignetteTitles: Cancerclass: An R package for development and validation of diagnostic tests from high-dimensional molecular data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cancerclass/inst/doc/vignette_cancerclass.R Package: CancerMutationAnalysis Version: 1.4.0 Depends: R (>= 2.10.0), qvalue Imports: AnnotationDbi, limma, methods, stats Suggests: KEGG.db License: GPL (>= 2) + file LICENSE Archs: i386, x64 MD5sum: c56b1d4ccd4d305f2727700c5733b637 NeedsCompilation: yes Title: Cancer mutation analysis Description: This package implements gene and gene-set level analysis methods for somatic mutation studies of cancer. The gene-level methods distinguish between driver genes (which play an active role in tumorigenesis) and passenger genes (which are mutated in tumor samples, but have no role in tumorigenesis) and incorporate a two-stage study design. The gene-set methods implement a patient-oriented approach, which calculates gene-set scores for each sample, then combines them across samples; a gene-oriented approach which uses the Wilcoxon test is also provided for comparison. biocViews: Genetics, Bioinformatics, Software Author: Giovanni Parmigiani, Simina M. Boca Maintainer: Simina M. Boca source.ver: src/contrib/CancerMutationAnalysis_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CancerMutationAnalysis_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CancerMutationAnalysis_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CancerMutationAnalysis_1.4.0.tgz vignettes: vignettes/CancerMutationAnalysis/inst/doc/CancerMutationAnalysis.pdf vignetteTitles: CancerMutationAnalysisTutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Package: casper Version: 1.1.2 Depends: R (>= 2.14.1), Biobase, IRanges, methods, gtools, GenomicRanges, Rsamtools, plyr, gaga Imports: VGAM, mgcv, GenomicFeatures, survival, sqldf Enhances: parallel License: GPL (>=2) Archs: i386, x64 MD5sum: bd9ab4d0003865b7ae24f139ae32c067 NeedsCompilation: yes Title: Characterization of Alternative Splicing based on Paired-End Reads Description: Infer alternative splicing from paired-end RNA-seq data. The model is based on counting paths across exons, rather than pairwise exon connections, and estimates the fragment size and start distributions non-parametrically, which improves estimation precision. biocViews: Bioinformatics, GeneExpression, DifferentialExpression, Transcription, RNASeq, HighThroughputSequencing Author: David Rossell, Camille Stephan-Otto, Manuel Kroiss Maintainer: David Rossell source.ver: src/contrib/casper_1.1.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/casper_1.1.2.zip win64.binary.ver: bin/windows64/contrib/2.16/casper_1.1.2.zip mac.binary.ver: bin/macosx/contrib/2.16/casper_1.1.2.tgz vignettes: vignettes/casper/inst/doc/casper.pdf vignetteTitles: Manual for the casper library hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/casper/inst/doc/casper.R Package: Category Version: 2.26.0 Depends: BiocGenerics (>= 0.3.2), AnnotationDbi (>= 0.1.15), Biobase (>= 2.17.8), methods Imports: BiocGenerics, graph, methods, Biobase, AnnotationDbi, RBGL, GSEABase (>= 1.19.3), genefilter, annotate (>= 1.15.6), stats, utils Suggests: EBarrays, ALL, Rgraphviz, RColorBrewer, xtable (>= 1.4-6), hgu95av2.db, Matrix, KEGG.db, GO.db, SNPchip (>= 2.3.11), geneplotter, limma, lattice, graph, Biobase, genefilter, methods, RUnit, org.Sc.sgd.db, GOstats License: Artistic-2.0 MD5sum: d3bbe910160067511fc1e2728d0cc76a NeedsCompilation: no Title: Category Analysis Description: A collection of tools for performing category analysis. biocViews: Annotation, GO, Pathways, GeneSetEnrichment Author: R. Gentleman with contributions from S. Falcon and D.Sarkar Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Category_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Category_2.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Category_2.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Category_2.26.0.tgz vignettes: vignettes/Category/inst/doc/Category.pdf, vignettes/Category/inst/doc/ChromBand.pdf vignetteTitles: Using Categories to Analyze Microarray Data, Using Chromosome Bands as Categories hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Category/inst/doc/Category.R, vignettes/Category/inst/doc/ChromBand.R dependsOnMe: categoryCompare, GOstats, PCpheno importsMe: categoryCompare, cellHTS2, eisa, gCMAP, GOstats, PCpheno, phenoTest, ppiStats suggestsMe: BiocCaseStudies, cellHTS, MmPalateMiRNA Package: categoryCompare Version: 1.4.0 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), AnnotationDbi (>= 0.1.15), Category (>= 2.23.4) Imports: BiocGenerics, Biobase, AnnotationDbi, hwriter, GSEABase, Category, GOstats, annotate, colorspace, graph, RCytoscape (>= 1.5.11) Suggests: methods, GSEABase, hwriter, colorspace, graph, GO.db, KEGG.db, estrogen, org.Hs.eg.db, hgu95av2.db, limma, affy, genefilter License: GPL-2 MD5sum: 7a373ca7810716710950535c0aa389ea NeedsCompilation: no Title: Meta-analysis of high-throughput experiments using feature annotations Description: Calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested). biocViews: Bioinformatics, Annotation, GO, MultipleComparisons, Pathways, GeneExpression Author: Robert M. Flight Maintainer: Robert M. Flight SystemRequirements: Cytoscape (>= 2.8.0) (if used for visualization of results, heavily suggested), CytoscapeRPC plugin (>= 1.8) source.ver: src/contrib/categoryCompare_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/categoryCompare_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/categoryCompare_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/categoryCompare_1.4.0.tgz vignettes: vignettes/categoryCompare/inst/doc/categoryCompare_vignette.pdf vignetteTitles: categoryCompare: High-throughput data meta-analysis using gene annotations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: cellGrowth Version: 1.4.0 Depends: R (>= 2.12.0), locfit (>= 1.5-4) Imports: lattice License: Artistic-2.0 MD5sum: ec9ad80bbd90a2a121602f106d6ccb07 NeedsCompilation: no Title: Fitting cell population growth models Description: This package provides functionalities for the fitting of cell population growth models on experimental OD curves. biocViews: CellBasedAssays, MicrotitrePlateAssay, DataImport, Visualization, TimeCourse Author: Julien Gagneur , Andreas Neudecker Maintainer: Julien Gagneur source.ver: src/contrib/cellGrowth_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cellGrowth_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cellGrowth_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cellGrowth_1.4.0.tgz vignettes: vignettes/cellGrowth/inst/doc/cellGrowth.pdf, vignettes/cellGrowth/inst/doc/cellGrowth-platePlotex.pdf, vignettes/cellGrowth/inst/doc/cellGrowth-plotex.pdf, vignettes/cellGrowth/inst/doc/cellGrowth-welldatex.pdf vignetteTitles: Overview of the cellGrowth package., cellGrowth-platePlotex.pdf, cellGrowth-plotex.pdf, cellGrowth-welldatex.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellGrowth/inst/doc/cellGrowth.R Package: cellHTS Version: 1.30.0 Depends: R (>= 2.10), prada (>= 1.9.4), RColorBrewer, Biobase (>= 1.11.12), genefilter (>= 1.11.2) Suggests: Category, GO.db, vsn (>= 2.0.35) License: Artistic-2.0 MD5sum: c1d6f628f083ba435d2e7e0126ca65f0 NeedsCompilation: no Title: Analysis of cell-based screens Description: Analysis of cell-based RNA interference screens biocViews: CellBasedAssays, Visualization Author: Wolfgang Huber , Ligia Bras , Michael Boutros Maintainer: Ligia Bras URL: http://www.dkfz.de/signaling, http://www.ebi.ac.uk/huber source.ver: src/contrib/cellHTS_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cellHTS_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cellHTS_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cellHTS_1.30.0.tgz vignettes: vignettes/cellHTS/inst/doc/cellhts.pdf, vignettes/cellHTS/inst/doc/twoChannels.pdf, vignettes/cellHTS/inst/doc/twoWay.pdf vignetteTitles: Main vignette: End-to-end analysis of cell-based screens, Supplement: multi-channel assays, Supplement: two-way assays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellHTS/inst/doc/cellhts.R, vignettes/cellHTS/inst/doc/twoChannels.R, vignettes/cellHTS/inst/doc/twoWay.R suggestsMe: prada Package: cellHTS2 Version: 2.24.1 Depends: R (>= 2.10), RColorBrewer, Biobase, methods, genefilter, splots, vsn, hwriter, locfit, grid Imports: prada, GSEABase, Category, stats4 License: Artistic-2.0 MD5sum: dd5ee4ecd6167387d8aec6cfa691e2d0 NeedsCompilation: no Title: Analysis of cell-based screens - revised version of cellHTS Description: This package provides tools for the analysis of high-throughput assays that were performed in 384-well microtitre plate (or analogous) formats. The functionality includes data import and management, normalisation, quality assessment, replicate summarisation and statistical scoring. A webpage that provides a detailed graphical overview over the data and analysis results is produced. In our work, we have applied the package to RNAi screens on fly and human cells, and for screens of yeast libraries. See ?cellHTS2 for a brief introduction. biocViews: CellBasedAssays, Preprocessing, Visualization Author: Ligia Bras, Wolfgang Huber , Michael Boutros , Gregoire Pau , Florian Hahne Maintainer: Joseph Barry URL: http://www.dkfz.de/signaling, http://www.ebi.ac.uk/huber source.ver: src/contrib/cellHTS2_2.24.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/cellHTS2_2.24.1.zip win64.binary.ver: bin/windows64/contrib/2.16/cellHTS2_2.24.1.zip mac.binary.ver: bin/macosx/contrib/2.16/cellHTS2_2.24.1.tgz vignettes: vignettes/cellHTS2/inst/doc/cellhts2Complete.pdf, vignettes/cellHTS2/inst/doc/cellhts2.pdf, vignettes/cellHTS2/inst/doc/twoChannels.pdf, vignettes/cellHTS2/inst/doc/twoWay.pdf vignetteTitles: Main vignette (complete version): End-to-end analysis of cell-based screens, Main vignette: End-to-end analysis of cell-based screens, Supplement: multi-channel assays, Supplement: enhancer-suppressor screens hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellHTS2/inst/doc/cellhts2Complete.R, vignettes/cellHTS2/inst/doc/cellhts2.R, vignettes/cellHTS2/inst/doc/twoChannels.R, vignettes/cellHTS2/inst/doc/twoWay.R dependsOnMe: coRNAi, imageHTS, staRank importsMe: HTSanalyzeR, RNAinteract Package: CellNOptR Version: 1.6.0 Depends: R (>= 2.15.0), RBGL, graph, methods, hash, ggplot2, RCurl, Rgraphviz Suggests: RUnit, BiocGenerics, igraph License: GPL-2 Archs: i386, x64 MD5sum: 7f68dfbd0937c28ab4fb7641f027db9c NeedsCompilation: yes Title: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data. Description: This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network. biocViews: CellBasedAssays, CellBiology, Proteomics, Bioinformatics, TimeCourse Author: T.Cokelaer, F.Eduati, A.MacNamara, S.Schrier, C.Terfve Maintainer: T.Cokelaer SystemRequirements: Graphviz version >= 2.2 source.ver: src/contrib/CellNOptR_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CellNOptR_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CellNOptR_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CellNOptR_1.6.0.tgz vignettes: vignettes/CellNOptR/inst/doc/CellNOptR0_1flowchart.pdf, vignettes/CellNOptR/inst/doc/CellNOptR-vignette.pdf, vignettes/CellNOptR/inst/doc/Fig2.pdf, vignettes/CellNOptR/inst/doc/Fig3.pdf, vignettes/CellNOptR/inst/doc/Fig4.pdf, vignettes/CellNOptR/inst/doc/Fig6.pdf, vignettes/CellNOptR/inst/doc/Fig7.pdf, vignettes/CellNOptR/inst/doc/Fig8.pdf vignetteTitles: CellNOptR0_1flowchart.pdf, Main vignette:Playing with networks using CellNOptR, Fig2.pdf, Fig3.pdf, Fig4.pdf, Fig6.pdf, Fig7.pdf, Fig8.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CellNOptR/inst/doc/CellNOptR-vignette.R dependsOnMe: CNORdt, CNORfeeder, CNORfuzzy, CNORode Package: CGEN Version: 2.2.0 Depends: R (>= 2.10.1), survival Suggests: cluster License: GPL-2 + file LICENSE Archs: i386, x64 MD5sum: 05e641b2fa405fccc23f6481237409ba NeedsCompilation: yes Title: An R package for analysis of case-control studies in genetic epidemiology Description: An R package for analysis of case-control studies in genetic epidemiology biocViews: SNP, MultipleComparisons, Clustering Author: Samsiddhi Bhattacharjee, Nilanjan Chatterjee, Summer Han and William Wheeler Maintainer: William Wheeler source.ver: src/contrib/CGEN_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CGEN_2.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CGEN_2.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CGEN_2.2.0.tgz vignettes: vignettes/CGEN/inst/doc/vignette.pdf vignetteTitles: CGEN Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/CGEN/inst/doc/vignette.R Package: CGHbase Version: 1.20.0 Depends: R (>= 2.10), methods, Biobase (>= 2.5.5), marray License: GPL MD5sum: 91ca42cb11fd0a392ba4249c403b5944 NeedsCompilation: no Title: CGHbase: Base functions and classes for arrayCGH data analysis. Description: Contains functions and classes that are needed by arrayCGH packages. biocViews: Infrastructure, Microarray, CopyNumberVariants Author: Sjoerd Vosse, Mark van de Wiel Maintainer: Mark van de Wiel source.ver: src/contrib/CGHbase_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CGHbase_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CGHbase_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CGHbase_1.20.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: CGHcall, CGHnormaliter, CGHregions, sigaR importsMe: CGHnormaliter, plrs Package: CGHcall Version: 2.20.0 Depends: R (>= 2.0.0), impute(>= 1.8.0), DNAcopy (>= 1.6.0), methods, Biobase, CGHbase (>= 1.15.1), snowfall License: GPL (http://www.gnu.org/copyleft/gpl.html) MD5sum: 75aa2c29a4ea2d448b79534f4f091586 NeedsCompilation: no Title: Calling aberrations for array CGH tumor profiles. Description: Calls aberrations for array CGH data using a six state mixture model as well as several biological concepts that are ignored by existing algorithms. Visualization of profiles is also provided. biocViews: Microarray,Preprocessing,Visualization Author: Mark van de Wiel, Sjoerd Vosse Maintainer: Mark van de Wiel source.ver: src/contrib/CGHcall_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CGHcall_2.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CGHcall_2.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CGHcall_2.20.0.tgz vignettes: vignettes/CGHcall/inst/doc/CGHcall.pdf vignetteTitles: CGHcall hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHcall/inst/doc/CGHcall.R dependsOnMe: CGHnormaliter importsMe: CGHnormaliter Package: cghMCR Version: 1.18.0 Depends: methods, DNAcopy, CNTools, limma Imports: BiocGenerics (>= 0.1.6), stats4 License: LGPL MD5sum: 46d079e2a33e5bfacf773518a73f7417 NeedsCompilation: no Title: Find chromosome regions showing common gains/losses Description: This package provides functions to identify genomic regions of interests based on segmented copy number data from multiple samples. biocViews: Microarray, CopyNumberVariants Author: J. Zhang and B. Feng Maintainer: J. Zhang source.ver: src/contrib/cghMCR_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cghMCR_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cghMCR_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cghMCR_1.18.0.tgz vignettes: vignettes/cghMCR/inst/doc/findMCR.pdf vignetteTitles: cghMCR findMCR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cghMCR/inst/doc/findMCR.R Package: CGHnormaliter Version: 1.14.0 Depends: CGHcall (>= 2.17.0), CGHbase (>= 1.15.0) Imports: Biobase, CGHbase, CGHcall, methods, stats, utils License: GPL (>= 3) MD5sum: e96737676ef6bafb72a4847ec217e8c6 NeedsCompilation: no Title: Normalization of array CGH data with imbalanced aberrations. Description: Normalization and centralization of array comparative genomic hybridization (aCGH) data. The algorithm uses an iterative procedure that effectively eliminates the influence of imbalanced copy numbers. This leads to a more reliable assessment of copy number alterations (CNAs). biocViews: Microarray, Preprocessing Author: Bart P.P. van Houte, Thomas W. Binsl, Hannes Hettling Maintainer: Bart P.P. van Houte source.ver: src/contrib/CGHnormaliter_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CGHnormaliter_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CGHnormaliter_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CGHnormaliter_1.14.0.tgz vignettes: vignettes/CGHnormaliter/inst/doc/CGHnormaliter-method.pdf, vignettes/CGHnormaliter/inst/doc/CGHnormaliter.pdf vignetteTitles: CGHnormaliter-method.pdf, CGHnormaliter hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHnormaliter/inst/doc/CGHnormaliter.R Package: CGHregions Version: 1.18.0 Depends: R (>= 2.0.0), methods, Biobase, CGHbase License: GPL (http://www.gnu.org/copyleft/gpl.html) MD5sum: 7e7aca07446e2d3713b5bd0d4b712823 NeedsCompilation: no Title: Dimension Reduction for Array CGH Data with Minimal Information Loss. Description: Dimension Reduction for Array CGH Data with Minimal Information Loss biocViews: Microarray,CopyNumberVariants,Visualization Author: Sjoerd Vosse & Mark van de Wiel Maintainer: Sjoerd Vosse source.ver: src/contrib/CGHregions_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CGHregions_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CGHregions_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CGHregions_1.18.0.tgz vignettes: vignettes/CGHregions/inst/doc/CGHregions.pdf vignetteTitles: CGHcall hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHregions/inst/doc/CGHregions.R suggestsMe: ADaCGH2 Package: charm Version: 2.6.0 Depends: R (>= 2.14.0), Biobase, SQN, fields, RColorBrewer, genefilter Imports: BSgenome, Biobase, oligo (>= 1.11.31), oligoClasses(>= 1.17.39), ff, preprocessCore, methods, stats, Biostrings, IRanges, siggenes, nor1mix, gtools, grDevices, graphics, utils, limma, parallel, sva(>= 3.1.2) Suggests: charmData, BSgenome.Hsapiens.UCSC.hg18, corpcor License: LGPL (>= 2) MD5sum: 5e4d35c2397cb15b8f5a29e6386eb650 NeedsCompilation: no Title: Analysis of DNA methylation data from CHARM microarrays Description: This package implements analysis tools for DNA methylation data generated using Nimblegen microarrays and the McrBC protocol. It finds differentially methylated regions between samples, calculates percentage methylation estimates and includes array quality assessment tools. biocViews: Microarray, Bioinformatics, DNAMethylation Author: Martin Aryee, Peter Murakami, Harris Jaffee, Rafael Irizarry Maintainer: Peter Murakami source.ver: src/contrib/charm_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/charm_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/charm_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/charm_2.6.0.tgz vignettes: vignettes/charm/inst/doc/charm.pdf vignetteTitles: charm Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/charm/inst/doc/charm.R Package: ChemmineR Version: 2.12.3 Depends: R (>= 2.10.0), methods Imports: graphics, methods, stats, RCurl, DBI, digest, BiocGenerics Suggests: RSQLite, scatterplot3d, gplots, fmcsR License: Artistic-2.0 Archs: i386, x64 MD5sum: ad11dc1f14e3651771b07c0ed79b5139 NeedsCompilation: yes Title: Cheminformatics of Drug-like Small Molecule Data Description: ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures. biocViews: MicrotitrePlateAssay, CellBasedAssays, Visualization, Infrastructure, DataImport, Clustering, Bioinformatics, Proteomics Author: Y. Eddie Cao, Kevin Horan, Tyler Backman, Yan Wang, Thomas Girke Maintainer: ChemmineR Team URL: http://manuals.bioinformatics.ucr.edu/home/chemminer source.ver: src/contrib/ChemmineR_2.12.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/ChemmineR_2.12.3.zip win64.binary.ver: bin/windows64/contrib/2.16/ChemmineR_2.12.3.zip mac.binary.ver: bin/macosx/contrib/2.16/ChemmineR_2.12.3.tgz vignettes: vignettes/ChemmineR/inst/doc/ChemmineR.pdf vignetteTitles: gpls Tutorial hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChemmineR/inst/doc/ChemmineR.R dependsOnMe: eiR, fmcsR Package: chimera Version: 1.2.6 Depends: Biobase, GenomicRanges, Rsamtools, methods, org.Hs.eg.db, org.Mm.eg.db, AnnotationDbi, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene Suggests: BSgenome.Mmusculus.UCSC.mm9, TxDb.Mmusculus.UCSC.mm9.knownGene Enhances: Rsubread License: Artistic-2.0 MD5sum: 3e36558d5362e79794c365d40c4f28ee NeedsCompilation: no Title: A package for secondary analysis of fusion products Description: This package facilitates the characterisation of fusion products events. It allows to import fusion data results from the following fusion finders: bellerophontes, deFuse, FusionFinder, FusionHunter, mapSplice, tophat-fusion, FusionMap biocViews: Infrastructure Author: Raffaele A Calogero, Matteo Carrara, Marco Beccuti, Francesca Cordero Maintainer: Raffaele A Calogero SystemRequirements: TopHat, bowtie and samtools are required for some functionalities source.ver: src/contrib/chimera_1.2.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/chimera_1.2.6.zip win64.binary.ver: bin/windows64/contrib/2.16/chimera_1.2.6.zip mac.binary.ver: bin/macosx/contrib/2.16/chimera_1.2.6.tgz vignettes: vignettes/chimera/inst/doc/chimera.pdf vignetteTitles: chimera hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chimera/inst/doc/chimera.R dependsOnMe: oneChannelGUI Package: ChIPpeakAnno Version: 2.8.0 Depends: R (>= 2.10), grid,VennDiagram, BiocGenerics (>= 0.1.0), biomaRt, multtest, IRanges, Biostrings, BSgenome, BSgenome.Ecoli.NCBI.20080805, GO.db, org.Hs.eg.db, limma, GenomicFeatures Imports: gplots, BiocGenerics, biomaRt, multtest, IRanges, Biostrings, BSgenome, GO.db, limma, AnnotationDbi, GenomicFeatures Suggests: reactome.db, RUnit, BiocGenerics License: GPL (>= 2) MD5sum: aef3ca4a238b95d46c69a22a4b80fdac NeedsCompilation: no Title: Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments or any experiments resulted in large number of chromosome ranges. Description: The package includes functions to retrieve the sequences around the peak, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. Starting 2.0.5, new functions have been added for finding the peaks with bi-directional promoters with summary statistics (peaksNearBDP), for summarizing the occurrence of motifs in peaks (summarizePatternInPeaks) and for adding other IDs to annotated peaks or enrichedGO (addGeneIDs). This package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages biocViews: Annotation, ChIPseq, ChIPchip Author: Lihua Julie Zhu, Herve Pages, Claude Gazin, Nathan Lawson, Jianhong Ou, Simon Lin, David Lapointe and Michael Green Maintainer: Lihua Julie Zhu source.ver: src/contrib/ChIPpeakAnno_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ChIPpeakAnno_2.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ChIPpeakAnno_2.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ChIPpeakAnno_2.8.0.tgz vignettes: vignettes/ChIPpeakAnno/inst/doc/ChIPpeakAnno.pdf vignetteTitles: ChIPpeakAnno Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPpeakAnno/inst/doc/ChIPpeakAnno.R dependsOnMe: REDseq importsMe: FunciSNP, REDseq suggestsMe: oneChannelGUI, RIPSeeker Package: chipseq Version: 1.10.1 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.4), GenomicRanges (>= 1.7.7), BSgenome, ShortRead Imports: methods, BiocGenerics, IRanges, BSgenome, GenomicRanges, lattice, ShortRead, stats Suggests: GenomicFeatures, BSgenome.Mmusculus.UCSC.mm9, TxDb.Mmusculus.UCSC.mm9.knownGene License: Artistic-2.0 Archs: i386, x64 MD5sum: 9791c5795639d70537a1f8de084923fe NeedsCompilation: yes Title: chipseq: A package for analyzing chipseq data Description: Tools for helping process short read data for chipseq experiments biocViews: ChIPseq Author: Deepayan Sarkar, Robert Gentleman, Michael Lawrence, Zizhen Yao Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/chipseq_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/chipseq_1.10.1.zip win64.binary.ver: bin/windows64/contrib/2.16/chipseq_1.10.1.zip mac.binary.ver: bin/macosx/contrib/2.16/chipseq_1.10.1.tgz vignettes: vignettes/chipseq/inst/doc/Workflow.pdf vignetteTitles: A Sample ChIP-Seq analysis workflow hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chipseq/inst/doc/Workflow.R dependsOnMe: PING importsMe: HTSeqGenie suggestsMe: ggbio, oneChannelGUI Package: ChIPseqR Version: 1.14.0 Depends: R (>= 2.10.0), methods, BiocGenerics, ShortRead Imports: Biostrings, fBasics, GenomicRanges, graphics, grDevices, HilbertVis, IRanges, methods, ShortRead, stats, timsac, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: e1657e2681d61228d19cc80325e6b4a8 NeedsCompilation: yes Title: Identifying Protein Binding Sites in High-Throughput Sequencing Data Description: ChIPseqR identifies protein binding sites from ChIP-seq and nucleosome positioning experiments. The model used to describe binding events was developed to locate nucleosomes but should flexible enough to handle other types of experiments as well. biocViews: ChIPseq, Bioinformatics, Infrastructure Author: Peter Humburg Maintainer: Peter Humburg source.ver: src/contrib/ChIPseqR_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ChIPseqR_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ChIPseqR_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ChIPseqR_1.14.0.tgz vignettes: vignettes/ChIPseqR/inst/doc/Introduction.pdf vignetteTitles: Introduction to ChIPseqR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPseqR/inst/doc/Introduction.R Package: ChIPsim Version: 1.14.0 Depends: Biostrings Imports: IRanges, Biostrings, ShortRead, graphics, methods, stats, utils Suggests: actuar, zoo License: GPL (>= 2) MD5sum: d917dec9e962e4a906840d3c235795e3 NeedsCompilation: no Title: Simulation of ChIP-seq experiments Description: A general framework for the simulation of ChIP-seq data. Although currently focused on nucleosome positioning the package is designed to support different types of experiments. biocViews: Infrastructure, Bioinformatics, ChIPseq Author: Peter Humburg Maintainer: Peter Humburg source.ver: src/contrib/ChIPsim_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ChIPsim_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ChIPsim_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ChIPsim_1.14.0.tgz vignettes: vignettes/ChIPsim/inst/doc/ChIPsimIntro.pdf vignetteTitles: Simulating ChIP-seq experiments hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPsim/inst/doc/ChIPsimIntro.R Package: ChIPXpress Version: 1.2.0 Depends: R (>= 2.10), ChIPXpressData Imports: Biobase, GEOquery, frma, affy, bigmemory, biganalytics Suggests: mouse4302frmavecs, mouse4302.db, mouse4302cdf, RUnit, BiocGenerics License: GPL(>=2) MD5sum: 575a2d1bbbc96d9863b76463d6a65ad2 NeedsCompilation: no Title: ChIPXpress: enhanced transcription factor target gene identification from ChIP-seq and ChIP-chip data using publicly available gene expression profiles Description: ChIPXpress takes as input predicted TF bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target. biocViews: ChIPchip, ChIPseq, Bioinformatics Author: George Wu Maintainer: George Wu source.ver: src/contrib/ChIPXpress_1.2.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/ChIPXpress_1.2.0.tgz vignettes: vignettes/ChIPXpress/inst/doc/ChIPXpress.pdf vignetteTitles: ChIPXpress hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPXpress/inst/doc/ChIPXpress.R Package: chopsticks Version: 1.24.2 Depends: R(>= 2.10.0), survival, methods Suggests: hexbin License: GPL-3 Archs: i386, x64 MD5sum: b18f65f8868c14b684fa01b3004df538 NeedsCompilation: yes Title: The snp.matrix and X.snp.matrix classes Description: Implements classes and methods for large-scale SNP association studies biocViews: Microarray, SNPsAndGeneticVariability, SNP, GeneticVariability Author: Hin-Tak Leung Maintainer: Hin-Tak Leung URL: http://outmodedbonsai.sourceforge.net/ source.ver: src/contrib/chopsticks_1.24.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/chopsticks_1.24.2.zip win64.binary.ver: bin/windows64/contrib/2.16/chopsticks_1.24.2.zip mac.binary.ver: bin/macosx/contrib/2.16/chopsticks_1.24.2.tgz vignettes: vignettes/chopsticks/inst/doc/chopsticks-vignette.pdf, vignettes/chopsticks/inst/doc/snpMatrix-4d.pdf, vignettes/chopsticks/inst/doc/snpMatrix-paper-HumanHeridity2007.pdf, vignettes/chopsticks/inst/doc/snpStatsBug_1.3.6_-vignette.pdf, vignettes/chopsticks/inst/doc/snpStatsBug_1.5.4_-vignette.pdf, vignettes/chopsticks/inst/doc/snpStatsBug-vignette.pdf vignetteTitles: snpMatrix, snpMatrix-4d.pdf, snpMatrix-paper-HumanHeridity2007.pdf, snpStatsBug_1.3.6_-vignette.pdf, snpStatsBug_1.5.4_-vignette.pdf, snpStatsBug-vignette.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chopsticks/inst/doc/chopsticks-vignette.R Package: chroGPS Version: 1.3.3 Depends: R (>= 2.13.0), IRanges, methods, Biobase, MASS, graphics, stats, rgl, changepoint Imports: graphics, cluster, DPpackage, ICSNP Enhances: parallel, XML License: GPL (>=2) MD5sum: a264088bdb36346d5111015b96d5ff6d NeedsCompilation: no Title: chroGPS: visualizing the epigenome Description: We provide intuitive maps to visualize the association between genetic elements, with emphasis on epigenetics. The approach is based on Multi-Dimensional Scaling. We provide several sensible distance metrics, and adjustment procedures to remove systematic biases typically observed when merging data obtained under different technologies or genetic backgrounds. biocViews: Visualization, Clustering Author: Oscar Reina, David Rossell Maintainer: Oscar Reina source.ver: src/contrib/chroGPS_1.3.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/chroGPS_1.3.3.zip win64.binary.ver: bin/windows64/contrib/2.16/chroGPS_1.3.3.zip mac.binary.ver: bin/macosx/contrib/2.16/chroGPS_1.3.3.tgz vignettes: vignettes/chroGPS/inst/doc/chroGPS.pdf vignetteTitles: Manual for the chroGPS library hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chroGPS/inst/doc/chroGPS.R Package: ChromHeatMap Version: 1.14.0 Depends: R (>= 2.9.0), BiocGenerics (>= 0.3.2), annotate (>= 1.20.0), AnnotationDbi (>= 1.4.0), hgu95av2.db Imports: BiocGenerics, annotate, AnnotationDbi, Biobase (>= 2.17.8), graphics, grDevices, methods, stats, IRanges, rtracklayer Suggests: ALL License: Artistic-2.0 MD5sum: e7a8a11674ebf5a92a85aac925769387 NeedsCompilation: no Title: Heat map plotting by genome coordinate Description: The ChromHeatMap package can be used to plot genome-wide data (e.g. expression, CGH, SNP) along each strand of a given chromosome as a heat map. The generated heat map can be used to interactively identify probes and genes of interest. biocViews: Visualization Author: Tim F. Rayner Maintainer: Tim F. Rayner source.ver: src/contrib/ChromHeatMap_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ChromHeatMap_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ChromHeatMap_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ChromHeatMap_1.14.0.tgz vignettes: vignettes/ChromHeatMap/inst/doc/ChromHeatMap.pdf vignetteTitles: Plotting expression data with ChromHeatMap hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChromHeatMap/inst/doc/ChromHeatMap.R Package: cisPath Version: 1.0.6 Depends: R (>= 2.10.0), methods Imports: methods, utils License: GPL (>= 3) Archs: i386, x64 MD5sum: 85c03631910b50c52d547579445c3d6b NeedsCompilation: yes Title: Visualization and manage of the protein-protein interaction networks. Description: cisPath is an R package that uses web browsers to visualize and manage protein-protein interaction networks. biocViews: Proteomics Author: Likun Wang Maintainer: Likun Wang source.ver: src/contrib/cisPath_1.0.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/cisPath_1.0.6.zip win64.binary.ver: bin/windows64/contrib/2.16/cisPath_1.0.6.zip mac.binary.ver: bin/macosx/contrib/2.16/cisPath_1.0.6.tgz vignettes: vignettes/cisPath/inst/doc/cisPath.pdf vignetteTitles: cisPath hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cisPath/inst/doc/cisPath.R Package: clippda Version: 1.10.0 Depends: R (>= 2.13.1),limma, statmod, rgl, lattice, scatterplot3d, graphics, grDevices, stats, utils, Biobase, tools, methods License: GPL (>=2) MD5sum: 7d773a2d450308bc7b4ec8fef55cf057 NeedsCompilation: no Title: A package for the clinical proteomic profiling data analysis Description: Methods for the nalysis of data from clinical proteomic profiling studies. The focus is on the studies of human subjects, which are often observational case-control by design and have technical replicates. A method for sample size determination for planning these studies is proposed. It incorporates routines for adjusting for the expected heterogeneities and imbalances in the data and the within-sample replicate correlations. biocViews: Proteomics, OneChannel, DataPreprocessing,Bioinformatics,DifferentialExpression, MultipleComparisons, SampleSize Author: Stephen Nyangoma Maintainer: Stephen Nyangoma URL: http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml source.ver: src/contrib/clippda_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/clippda_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/clippda_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/clippda_1.10.0.tgz vignettes: vignettes/clippda/inst/doc/clippda.pdf vignetteTitles: Sample Size Calculation hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clippda/inst/doc/clippda.R Package: clipper Version: 1.0.0 Depends: R (>= 2.15.0), Matrix, graph Imports: methods, Biobase, igraph, gRbase (>= 1.6.6), qpgraph, KEGGgraph, corpcor, RBGL Suggests: RUnit, BiocGenerics, RCytoscape (>= 1.6.3), graphite, ALL, hgu95av2.db License: AGPL-3 MD5sum: b5f24e16df47be5fc1e85fb829c0a491 NeedsCompilation: no Title: Gene set analysis exploiting pathway topology Description: clipper is a package for topological gene set analysis. It implements a two-step empirical approach based on the exploitation of graph decomposition into a junction tree to reconstruct the most relevant signal path. In the first step clipper selects significant pathways according to statistical tests on the means and the concentration matrices of the graphs derived from pathway topologies. Then, it "clips" the whole pathway identifying the signal paths having the greatest association with a specific phenotype. Author: Paolo Martini , Gabriele Sales , Chiara Romualdi Maintainer: Paolo Martini source.ver: src/contrib/clipper_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/clipper_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/clipper_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/clipper_1.0.0.tgz vignettes: vignettes/clipper/inst/doc/clipper.pdf vignetteTitles: clipper hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clipper/inst/doc/clipper.R suggestsMe: graphite Package: Clonality Version: 1.8.0 Depends: R (>= 2.12.2), DNAcopy Imports: DNAcopy, grDevices, graphics, stats, utils Suggests: gdata, DNAcopy License: GPL-3 MD5sum: 32aef04394ddfe3f7bb415c192161b75 NeedsCompilation: no Title: Clonality testing Description: Statistical tests for clonality versus independence of tumors from the same patient based on their LOH or genomewide copy number profiles biocViews: Microarray, CopyNumberVariants, Classification, aCGH Author: Irina Ostrovnaya Maintainer: Irina Ostrovnaya source.ver: src/contrib/Clonality_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Clonality_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Clonality_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Clonality_1.8.0.tgz vignettes: vignettes/Clonality/inst/doc/Clonality.pdf vignetteTitles: Clonality hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Clonality/inst/doc/Clonality.R Package: clst Version: 1.8.0 Depends: R (>= 2.10) Imports: ROC, lattice Suggests: RUnit License: GPL-3 MD5sum: 2823434042ed794f0507a9f39253577a NeedsCompilation: no Title: Classification by local similarity threshold Description: Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons. biocViews: Classification Author: Noah Hoffman Maintainer: Noah Hoffman source.ver: src/contrib/clst_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/clst_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/clst_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/clst_1.8.0.tgz vignettes: vignettes/clst/inst/doc/clstDemo.pdf, vignettes/clst/inst/doc/matchtypes.pdf vignetteTitles: clst, matchtypes.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clst/inst/doc/clstDemo.R dependsOnMe: clstutils Package: clstutils Version: 1.8.0 Depends: R (>= 2.10), clst, rjson, ape Imports: lattice, RSQLite Suggests: RUnit, RSVGTipsDevice License: GPL-3 MD5sum: 6b3225359adbd96cdba31965be595cf7 NeedsCompilation: no Title: Tools for performing taxonomic assignment. Description: Tools for performing taxonomic assignment based on phylogeny using pplacer and clst. biocViews: HighThroughputSequencing, Classification, Visualization, QualityControl Author: Noah Hoffman Maintainer: Noah Hoffman source.ver: src/contrib/clstutils_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/clstutils_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/clstutils_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/clstutils_1.8.0.tgz vignettes: vignettes/clstutils/inst/doc/pplacerDemo.pdf, vignettes/clstutils/inst/doc/refSet.pdf vignetteTitles: clst, clstutils hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clstutils/inst/doc/pplacerDemo.R, vignettes/clstutils/inst/doc/refSet.R Package: clusterProfiler Version: 1.8.0 Depends: R (>= 2.10), ggplot2 Imports: methods, stats4, DBI, plyr, AnnotationDbi, GO.db, KEGG.db, org.Hs.eg.db, DOSE Suggests: GOSemSim, ReactomePA License: Artistic-2.0 MD5sum: ed6f355502fabcc413a940ade60ecf2d NeedsCompilation: no Title: statistical analysis and visulization of functional profiles for genes and gene clusters Description: The package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters. biocViews: Clustering, GO, Pathways, Visualization, MultipleComparisons, GeneSetEnrichment Author: Guangchuang Yu, Li-Gen Wang Maintainer: Guangchuang Yu URL: http://online.liebertpub.com/doi/abs/10.1089/omi.2011.0118 source.ver: src/contrib/clusterProfiler_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/clusterProfiler_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/clusterProfiler_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/clusterProfiler_1.8.0.tgz vignettes: vignettes/clusterProfiler/inst/doc/clusterProfiler_for_unsupported_organisms.pdf, vignettes/clusterProfiler/inst/doc/clusterProfiler.pdf, vignettes/clusterProfiler/inst/doc/omics2012.pdf vignetteTitles: clusterProfiler_for_unsupported_organisms.pdf, An introduction to clusterProfiler, omics2012.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clusterProfiler/inst/doc/clusterProfiler.R suggestsMe: DOSE, GOSemSim, ReactomePA Package: clusterStab Version: 1.32.0 Depends: Biobase (>= 1.4.22), R (>= 1.9.0), methods Suggests: fibroEset, genefilter License: Artistic-2.0 MD5sum: 3938bbbb7cb2618d0b7f085d00ac4a69 NeedsCompilation: no Title: Compute cluster stability scores for microarray data Description: This package can be used to estimate the number of clusters in a set of microarray data, as well as test the stability of these clusters. biocViews: Clustering Author: James W. MacDonald, Debashis Ghosh, Mark Smolkin Maintainer: James W. MacDonald source.ver: src/contrib/clusterStab_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/clusterStab_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/clusterStab_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/clusterStab_1.32.0.tgz vignettes: vignettes/clusterStab/inst/doc/clusterStab.pdf vignetteTitles: clusterStab Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clusterStab/inst/doc/clusterStab.R Package: CMA Version: 1.18.0 Depends: R (>= 2.10), methods, stats, Biobase Suggests: MASS, class, nnet, glmnet, e1071, randomForest, plsgenomics, gbm, mgcv, corpcor, limma, st License: GPL (>= 2) MD5sum: 88d5f357a44754db90bc4b419eb7248a NeedsCompilation: no Title: Synthesis of microarray-based classification Description: This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment. biocViews: Classification Author: Martin Slawski , Anne-Laure Boulesteix , Christoph Bernau . Maintainer: Christoph Bernau source.ver: src/contrib/CMA_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CMA_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CMA_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CMA_1.18.0.tgz vignettes: vignettes/CMA/inst/doc/CMA_vignette.pdf vignetteTitles: CMA_vignette.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CMA/inst/doc/CMA_vignette.R Package: CNAnorm Version: 1.6.0 Depends: R (>= 2.10.1), DNAcopy, methods Imports: methods License: GPL-2 Archs: i386, x64 MD5sum: f0fc2b7a976d1082039dff2999aa32ea NeedsCompilation: yes Title: A normalization method for Copy Number Aberration in cancer samples Description: Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. It performs a "discrete" normalization looking for the ploidy of the genome. It will also provide tumour content if at least two ploidy states can be found. biocViews: Bioinformatics, HighThroughputSequencing, CopyNumberVariants, Sequencing, Cancer, Lung Author: Stefano Berri , Henry M. Wood , Arief Gusnanto Maintainer: Stefano Berri URL: http://www.r-project.org, source.ver: src/contrib/CNAnorm_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNAnorm_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNAnorm_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNAnorm_1.6.0.tgz vignettes: vignettes/CNAnorm/inst/doc/CNAnorm.pdf vignetteTitles: CNAnorm.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: cn.farms Version: 1.8.0 Depends: R (>= 2.11), Biobase, methods, ff, oligoClasses, snow Imports: BiocGenerics, DBI, affxparser, oligo, DNAcopy, preprocessCore, lattice Suggests: pd.mapping250k.sty, pd.mapping250k.nsp, pd.genomewidesnp.5, pd.genomewidesnp.6 License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: 2b2ad36339862a5c6d1a05a58a509e85 NeedsCompilation: yes Title: cn.farms - factor analysis for copy number estimation Description: This package implements the cn.FARMS algorithm for copy number variation (CNV) analysis. cn.FARMS allows to analyze the most common Affymetrix (250K-SNP6.0) array types, supports high-performance computing using snow and ff. biocViews: Microarray, Bioinformatics, CopyNumberVariants Author: Andreas Mitterecker, Djork-Arne Clevert Maintainer: Andreas Mitterecker URL: http://www.bioinf.jku.at/software/cnfarms/cnfarms.html source.ver: src/contrib/cn.farms_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cn.farms_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cn.farms_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cn.farms_1.8.0.tgz vignettes: vignettes/cn.farms/inst/doc/cn.farms.pdf vignetteTitles: cn.farms: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cn.farms/inst/doc/cn.farms.R Package: cn.mops Version: 1.6.7 Depends: R (>= 2.12), BiocGenerics, Biobase, IRanges, GenomicRanges Imports: methods, graphics, BiocGenerics, IRanges, Rsamtools, Suggests: snow, DNAcopy License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: 8c11c9981c41e71fd510b3b5dc19df50 NeedsCompilation: yes Title: cn.mops - Mixture of Poissons for CNV detection in NGS data Description: cn.mops (Copy Number estimation by a Mixture Of PoissonS) is a data processing pipeline for copy number variations and aberrations (CNVs and CNAs) from next generation sequencing (NGS) data. The package supplies functions to convert BAM files into read count matrices or genomic ranges objects, which are the input objects for cn.mops. cn.mops models the depths of coverage across samples at each genomic position. Therefore, it does not suffer from read count biases along chromosomes. Using a Bayesian approach, cn.mops decomposes read variations across samples into integer copy numbers and noise by its mixture components and Poisson distributions, respectively. cn.mops guarantees a low FDR because wrong detections are indicated by high noise and filtered out. cn.mops is very fast and written in C++. biocViews: HighThroughputSequencing, Sequencing, Bioinformatics, CopyNumberVariants, Homo_sapiens, CellBiology, HighTroughputSequencingData, HapMap, Genetics Author: Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/cnmops/cnmops.html source.ver: src/contrib/cn.mops_1.6.7.tar.gz win.binary.ver: bin/windows/contrib/2.16/cn.mops_1.6.7.zip win64.binary.ver: bin/windows64/contrib/2.16/cn.mops_1.6.7.zip mac.binary.ver: bin/macosx/contrib/2.16/cn.mops_1.6.7.tgz vignettes: vignettes/cn.mops/inst/doc/cn.mops.pdf vignetteTitles: cn.mops: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cn.mops/inst/doc/cn.mops.R Package: CNORdt Version: 1.2.0 Depends: R (>= 1.8.0), CellNOptR (>= 0.99), abind License: GPL-2 Archs: i386, x64 MD5sum: 1c5383ee9e467a8000f774fbebeb8d6c NeedsCompilation: yes Title: Add-on to CellNOptR: Discretized time treatments Description: This add-on to the package CellNOptR handles time-course data, as opposed to steady state data in CellNOptR. It scales the simulation step to allow comparison and model fitting for time-course data. Future versions will optimize delays and strengths for each edge. biocViews: CellBasedAssays, CellBiology, Proteomics, Bioinformatics, TimeCourse Author: A. MacNamara Maintainer: A. MacNamara source.ver: src/contrib/CNORdt_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNORdt_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNORdt_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNORdt_1.2.0.tgz vignettes: vignettes/CNORdt/inst/doc/CNORdt-vignette.pdf, vignettes/CNORdt/inst/doc/CNORdt-vignette-plot.pdf vignetteTitles: Using multiple time points to train logic models to data, CNORdt-vignette-plot.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORdt/inst/doc/CNORdt-vignette.R Package: CNORfeeder Version: 1.0.0 Depends: R (>= 2.15.0), CellNOptR (>= 1.4.0), graph Suggests: minet, catnet, igraph, Rgraphviz, RUnit, BiocGenerics License: GPL-3 MD5sum: 2785ebd69b6a69ed7538cae9ce00d7eb NeedsCompilation: no Title: Integration of CellNOptR to add missing links Description: This package integrates literature-constrained and data-driven methods to infer signalling networks from perturbation experiments. It permits to extends a given network with links derived from the data via various inference methods, and uses information on physical interactions of proteins to guide and validate the integration of links. biocViews: CellBasedAssays, CellBiology, Proteomics, Bioinformatics, NetworkInference Author: F.Eduati Maintainer: F.Eduati source.ver: src/contrib/CNORfeeder_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNORfeeder_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNORfeeder_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNORfeeder_1.0.0.tgz vignettes: vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.pdf, vignettes/CNORfeeder/inst/doc/DDN.pdf, vignettes/CNORfeeder/inst/doc/integratedModel.pdf, vignettes/CNORfeeder/inst/doc/optModel.pdf, vignettes/CNORfeeder/inst/doc/SimResultsT1_1.pdf vignetteTitles: Main vignette:Playing with networks using CNORfeeder, DDN.pdf, integratedModel.pdf, optModel.pdf, SimResultsT1_1.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.R Package: CNORfuzzy Version: 1.2.0 Depends: R (>= 2.15.0), CellNOptR (>= 1.4.0), nloptr (>= 0.8.5) Suggests: xtable, Rgraphviz, RUnit, BiocGenerics License: GPL-2 Archs: i386, x64 MD5sum: 96ed7e976bd30eb5180bda5f990b363d NeedsCompilation: yes Title: Addon to CellNOptR: Fuzzy Logic Description: This package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL). Author: M. Morris, T. Cokelaer Maintainer: T. Cokelaer source.ver: src/contrib/CNORfuzzy_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNORfuzzy_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNORfuzzy_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNORfuzzy_1.2.0.tgz vignettes: vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette-FullAnalysis2.pdf, vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette-FullAnalysis3.pdf, vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette-FullAnalysis.pdf, vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.pdf, vignettes/CNORfuzzy/inst/doc/tf1.pdf, vignettes/CNORfuzzy/inst/doc/tf2.pdf vignetteTitles: CNORfuzzy-vignette-FullAnalysis2.pdf, CNORfuzzy-vignette-FullAnalysis3.pdf, CNORfuzzy-vignette-FullAnalysis.pdf, Main vignette:Playing with networks using CNORfuzzyl, tf1.pdf, tf2.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.R Package: CNORode Version: 1.2.0 Depends: CellNOptR (>= 1.5.14), genalg Enhances: MEIGOR License: GPL-3 Archs: i386, x64 MD5sum: 401b027ab013f803149ffffd699966b8 NeedsCompilation: yes Title: ODE add-on to CellNOptR Description: ODE add-on to CellNOptR biocViews: CellBasedAssays, CellBiology, Proteomics, Bioinformatics, TimeCourse Author: David Henriques, Thomas Cokelaer Maintainer: David Henriques source.ver: src/contrib/CNORode_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNORode_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNORode_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNORode_1.2.0.tgz vignettes: vignettes/CNORode/inst/doc/CNORode-vignette.pdf, vignettes/CNORode/inst/doc/data_ToyModelMMB_FeddbackAnd.pdf vignetteTitles: Main vignette:Playing with networks using CNORode, data_ToyModelMMB_FeddbackAnd.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORode/inst/doc/CNORode-vignette.R Package: CNTools Version: 1.16.0 Depends: R (>= 2.10), methods, tools, stats, genefilter License: LGPL Archs: i386, x64 MD5sum: 9d28d9536d4818d7e9008f1bd979fd17 NeedsCompilation: yes Title: Convert segment data into a region by sample matrix to allow for other high level computational analyses. Description: This package provides tools to convert the output of segmentation analysis using DNAcopy to a matrix structure with overlapping segments as rows and samples as columns so that other computational analyses can be applied to segmented data biocViews: Microarray, CopyNumberVariants Author: Jianhua Zhang Maintainer: J. Zhang source.ver: src/contrib/CNTools_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNTools_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNTools_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNTools_1.16.0.tgz vignettes: vignettes/CNTools/inst/doc/HowTo.pdf vignetteTitles: NCTools HowTo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNTools/inst/doc/HowTo.R dependsOnMe: cghMCR Package: cnvGSA Version: 1.4.0 Depends: methods, brglm Suggests: cnvGSAdata, org.Hs.eg.db License: LGPL MD5sum: c970886dd43fa99e40b3788787ec708d NeedsCompilation: no Title: Gene Set Analysis of (Rare) Copy Number Variants Description: This package is intended to facilitate gene-set association with rare CNVs in case-control studies. biocViews: MultipleComparisons Author: Daniele Merico ; packaged by Robert Ziman Maintainer: Robert Ziman source.ver: src/contrib/cnvGSA_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cnvGSA_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cnvGSA_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cnvGSA_1.4.0.tgz vignettes: vignettes/cnvGSA/inst/doc/cnvGSA-vignette.pdf vignetteTitles: cnvGSA - Gene-Set Analysis of Rare Copy Number Variants hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cnvGSA/inst/doc/cnvGSA-vignette.R Package: CNVtools Version: 1.54.0 Depends: R (>= 2.10), survival License: GPL-3 Archs: i386, x64 MD5sum: 649e5c034dad7b248b09a300dc2ff537 NeedsCompilation: yes Title: A package to test genetic association with CNV data Description: This package is meant to facilitate the testing of Copy Number Variant data for genetic association, typically in case-control studies. biocViews: GeneticVariability Author: Chris Barnes and Vincent Plagnol Maintainer: Chris Barnes source.ver: src/contrib/CNVtools_1.54.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CNVtools_1.54.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CNVtools_1.54.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CNVtools_1.54.0.tgz vignettes: vignettes/CNVtools/inst/doc/CNVtools-vignette.pdf vignetteTitles: Copy Number Variation Tools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNVtools/inst/doc/CNVtools-vignette.R Package: CoCiteStats Version: 1.32.0 Depends: R (>= 2.0), org.Hs.eg.db Imports: AnnotationDbi License: CPL MD5sum: d57c9d517721a822fdf342f44bac7b06 NeedsCompilation: no Title: Different test statistics based on co-citation. Description: A collection of software tools for dealing with co-citation data. biocViews: Bioinformatics Author: B. Ding and R. Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/CoCiteStats_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CoCiteStats_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CoCiteStats_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CoCiteStats_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: codelink Version: 1.28.1 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), methods, Biobase (>= 2.17.8), limma Imports: BiocGenerics, annotate Suggests: genefilter, parallel License: GPL-2 MD5sum: 8cf47d1a3cb65b57aca8ca06c356d1e0 NeedsCompilation: no Title: Manipulation of Codelink Bioarrays data. Description: This packages allow reading into R of Codelink bioarray data exported as text from the Codelink software. Also includes some functions to ease the manipulation and pre-processing of data, such in background correction and normalization. biocViews: Microarray, OneChannel, DataImport, Preprocessing Author: Diego Diez Maintainer: Diego Diez URL: http://www.kuicr.kyoto-u.ac.jp/~diez source.ver: src/contrib/codelink_1.28.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/codelink_1.28.1.zip win64.binary.ver: bin/windows64/contrib/2.16/codelink_1.28.1.zip mac.binary.ver: bin/macosx/contrib/2.16/codelink_1.28.1.tgz vignettes: vignettes/codelink/inst/doc/codelink.pdf, vignettes/codelink/inst/doc/CodelinkSet.pdf vignetteTitles: codelink, CodelinkSet hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/codelink/inst/doc/codelink.R, vignettes/codelink/inst/doc/CodelinkSet.R Package: CoGAPS Version: 1.10.0 Depends: R (>= 2.9.0), R.utils (>= 1.2.4), gplots (>= 2.8.0) Imports: graphics, grDevices, methods, stats, utils License: GPL (== 2) MD5sum: 5a018e692aa98e8543a6118256eca654 NeedsCompilation: yes Title: Coordinated Gene Activity in Pattern Sets Description: Coordinated Gene Activity in Pattern Sets (CoGAPS) infers biological processes which are active in individual gene sets from corresponding microarray measurements. CoGAPS achieves this inference by combining a MCMC matrix decomposition algorithm (GAPS) with a novel statistic inferring activity on gene sets. biocViews: GeneExpression, Microarray, Bioinformatics Author: Elana J. Fertig Maintainer: Elana J. Fertig , Michael F. Ochs URL: http://sourceforge.net/p/cogapscpp/wiki/Home/ SystemRequirements: GAPS-JAGS (==1.0.2) source.ver: src/contrib/CoGAPS_1.10.0.tar.gz vignettes: vignettes/CoGAPS/inst/doc/CoGAPSUsersManual.pdf vignetteTitles: GAPS/CoGAPS Users Manual hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CoGAPS/inst/doc/CoGAPSUsersManual.R Package: coGPS Version: 1.4.0 Depends: R (>= 2.13.0) Imports: graphics, grDevices Suggests: limma License: GPL-2 MD5sum: a10bb13bff0141098f7996cfb51a6423 NeedsCompilation: no Title: cancer outlier Gene Profile Sets Description: Gene Set Enrichment Analysis of P-value based statistics for outlier gene detection in dataset merged from multiple studies biocViews: Microarray, Bioinformatics, DifferentialExpression Author: Yingying Wei, Michael Ochs Maintainer: Yingying Wei source.ver: src/contrib/coGPS_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/coGPS_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/coGPS_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/coGPS_1.4.0.tgz vignettes: vignettes/coGPS/inst/doc/coGPS.pdf vignetteTitles: coGPS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/coGPS/inst/doc/coGPS.R Package: ConsensusClusterPlus Version: 1.16.0 Imports: Biobase, ALL, graphics, stats, utils, cluster License: GPL version 2 MD5sum: e2f3498425e5a340ac8163eed534b9b1 NeedsCompilation: no Title: ConsensusClusterPlus Description: algorithm for determining cluster count and membership by stability evidence in unsupervised analysis biocViews: Software, Bioinformatics, Clustering Author: Matt Wilkerson , Peter Waltman Maintainer: Matt Wilkerson source.ver: src/contrib/ConsensusClusterPlus_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ConsensusClusterPlus_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ConsensusClusterPlus_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ConsensusClusterPlus_1.16.0.tgz vignettes: vignettes/ConsensusClusterPlus/inst/doc/ConsensusClusterPlus.pdf vignetteTitles: ConsensusClusterPlus Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: convert Version: 1.36.0 Depends: R (>= 2.6.0), Biobase (>= 1.15.33), limma (>= 1.7.0), marray, utils, methods License: LGPL MD5sum: 6582bc6ba90d4b515c42af3d2318a06b NeedsCompilation: no Title: Convert Microarray Data Objects Description: Define coerce methods for microarray data objects. biocViews: Infrastructure, Microarray, TwoChannel Author: Gordon Smyth , James Wettenhall , Yee Hwa (Jean Yang) , Martin Morgan Martin Morgan Maintainer: Yee Hwa (Jean) Yang URL: http://bioinf.wehi.edu.au/limma/convert.html source.ver: src/contrib/convert_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/convert_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/convert_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/convert_1.36.0.tgz vignettes: vignettes/convert/inst/doc/convert.pdf vignetteTitles: Converting Between Microarray Data Classes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/convert/inst/doc/convert.R dependsOnMe: maigesPack, TurboNorm suggestsMe: BiocCaseStudies, dyebias, OLIN Package: copa Version: 1.28.0 Depends: Biobase, methods Suggests: colonCA License: Artistic-2.0 Archs: i386, x64 MD5sum: fcbd2f783aaaa9a9bfd912bc63382a15 NeedsCompilation: yes Title: Functions to perform cancer outlier profile analysis. Description: COPA is a method to find genes that undergo recurrent fusion in a given cancer type by finding pairs of genes that have mutually exclusive outlier profiles. biocViews: OneChannel, TwoChannel, DifferentialExpression, Visualization Author: James W. MacDonald Maintainer: James W. MacDonald source.ver: src/contrib/copa_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/copa_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/copa_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/copa_1.28.0.tgz vignettes: vignettes/copa/inst/doc/copa.pdf vignetteTitles: copa Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/copa/inst/doc/copa.R Package: copynumber Version: 1.1.1 Depends: R (>= 2.10), BiocGenerics Imports: GenomicRanges, IRanges License: Artistic-2.0 MD5sum: 177b8e824665c6a46cb95075b7b8b4bf NeedsCompilation: no Title: Segmentation of single- and multi-track copy number data by penalized least squares regression. Description: Penalized least squares regression is applied to fit piecewise constant curves to copy number data to locate genomic regions of constant copy number. Procedures are available for individual segmentation of each sample, joint segmentation of several samples and joint segmentation of the two data tracks from SNP-arrays. Several plotting functions are available for visualization of the data and the segmentation results. biocViews: aCGH, SNP, CopyNumberVariants, Genetics, Visualization, Bioinformatics Author: Gro Nilsen, Knut Liestoel and Ole Christian Lingjaerde. Maintainer: Gro Nilsen source.ver: src/contrib/copynumber_1.1.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/copynumber_1.1.1.zip win64.binary.ver: bin/windows64/contrib/2.16/copynumber_1.1.1.zip mac.binary.ver: bin/macosx/contrib/2.16/copynumber_1.1.1.tgz vignettes: vignettes/copynumber/inst/doc/copynumber.pdf, vignettes/copynumber/inst/doc/overview.pdf vignetteTitles: copynumber.pdf, overview.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/copynumber/inst/doc/copynumber.R Package: Cormotif Version: 1.6.0 Depends: R (>= 2.12.0), affy, limma Imports: affy, graphics, grDevices License: GPL-2 MD5sum: 1b022876d770b1fca1890896e6e18fe4 NeedsCompilation: no Title: Correlation Motif Fit Description: It fits correlation motif model to multiple studies to detect study specific differential expression patterns. biocViews: Microarray, Bioinformatics, DifferentialExpression Author: Hongkai Ji, Yingying Wei Maintainer: Yingying Wei source.ver: src/contrib/Cormotif_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Cormotif_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Cormotif_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Cormotif_1.6.0.tgz vignettes: vignettes/Cormotif/inst/doc/CormotifVignette.pdf vignetteTitles: Cormotif Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Cormotif/inst/doc/CormotifVignette.R Package: CorMut Version: 1.2.0 Depends: methods, Biostrings, seqinr,igraph License: GPL-2 MD5sum: a610310679583bcc6145cb7ddcda3d68 NeedsCompilation: no Title: Detect the correlated mutations based on selection pressure Description: CorMut provides functions for computing kaks for individual sites or specific amino acids and detecting correlated mutations among them. Two methods are provided for detecting correlated mutations ,including conditional selection pressure and mutual information. The computation consists of two steps: First, the positive selection sites are detected; Second, the mutation correlations are computed among the positive selection sites. Note that the first step is optional. Meanwhile, CorMut facilitates the comparison of the correlated mutations between two conditions by the means of correlated mutation network. biocViews: Bioinformatics, Sequencing Author: Zhenpeng Li, Yang Huang, Yabo Ouyang, Yiming Shao, Liying Ma Maintainer: Zhenpeng Li source.ver: src/contrib/CorMut_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CorMut_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CorMut_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CorMut_1.2.0.tgz vignettes: vignettes/CorMut/inst/doc/CorMut.pdf vignetteTitles: CorMut hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CorMut/inst/doc/CorMut.R Package: coRNAi Version: 1.10.1 Depends: R (>= 2.10), cellHTS2, limma, locfit Imports: MASS, gplots, lattice, grDevices, graphics, stats License: Artistic-2.0 MD5sum: fc230d26c7f2e95abf17118ef2130190 NeedsCompilation: no Title: Analysis of co-knock-down RNAi data Description: Analysis of combinatorial cell-based RNAi screens biocViews: CellBasedAssays Author: Elin Axelsson Maintainer: Elin Axelsson SystemRequirements: Graphviz source.ver: src/contrib/coRNAi_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/coRNAi_1.10.1.zip win64.binary.ver: bin/windows64/contrib/2.16/coRNAi_1.10.1.zip mac.binary.ver: bin/macosx/contrib/2.16/coRNAi_1.10.1.tgz vignettes: vignettes/coRNAi/inst/doc/coRNAi.pdf vignetteTitles: coRNAi hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/coRNAi/inst/doc/coRNAi.R Package: CORREP Version: 1.26.0 Imports: e1071, stats Suggests: cluster, MASS License: GPL (>= 2) MD5sum: 148359a732d4ef6ddbf91daf9ae388f2 NeedsCompilation: no Title: Multivariate Correlation Estimator and Statistical Inference Procedures. Description: Multivariate correlation estimation and statistical inference. See package vignette. biocViews: Bioinformatics, Microarray, Clustering, GraphsAndNetworks Author: Dongxiao Zhu and Youjuan Li Maintainer: Dongxiao Zhu source.ver: src/contrib/CORREP_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CORREP_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CORREP_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CORREP_1.26.0.tgz vignettes: vignettes/CORREP/inst/doc/CORREP.pdf vignetteTitles: Multivariate Correlation Estimator hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CORREP/inst/doc/CORREP.R Package: cqn Version: 1.6.0 Depends: R (>= 2.10.0), mclust, nor1mix, stats, preprocessCore, splines, quantreg Imports: splines Suggests: scales, edgeR License: Artistic-2.0 MD5sum: 92fafe3a6d3378df6541ce5374f5d79f NeedsCompilation: no Title: Conditional quantile normalization Description: A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method. biocViews: RNAseq, Preprocessing, DifferentialExpression Author: Jean (Zhijin) Wu, Kasper Daniel Hansen Maintainer: Kasper Daniel Hansen source.ver: src/contrib/cqn_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cqn_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cqn_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cqn_1.6.0.tgz vignettes: vignettes/cqn/inst/doc/cqn.pdf vignetteTitles: CQN (Conditional Quantile Normalization) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cqn/inst/doc/cqn.R importsMe: tweeDEseq Package: CRImage Version: 1.8.0 Depends: EBImage, DNAcopy, aCGH Imports: MASS, e1071, foreach, sgeostat License: Artistic-2.0 MD5sum: 53a8150bac2d84b9be707a663bd7b5bb NeedsCompilation: no Title: CRImage a package to classify cells and calculate tumour cellularity Description: CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity. biocViews: CellBiology, Classification Author: Henrik Failmezger , Yinyin Yuan , Oscar Rueda , Florian Markowetz Maintainer: Henrik Failmezger , Yinyin Yuan source.ver: src/contrib/CRImage_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CRImage_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CRImage_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CRImage_1.8.0.tgz vignettes: vignettes/CRImage/inst/doc/cellularity2.pdf, vignettes/CRImage/inst/doc/CRImage.pdf, vignettes/CRImage/inst/doc/labeledImage.pdf, vignettes/CRImage/inst/doc/segmentedImage.pdf, vignettes/CRImage/inst/doc/segmentedImageRaw.pdf vignetteTitles: cellularity2.pdf, CRImage Manual, labeledImage.pdf, segmentedImage.pdf, segmentedImageRaw.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CRImage/inst/doc/CRImage.R Package: crlmm Version: 1.18.0 Depends: R (>= 2.14.0), oligoClasses (>= 1.21.12), preprocessCore (>= 1.17.7) Imports: methods, Biobase (>= 2.15.4), BiocGenerics, affyio (>= 1.23.2), illuminaio, ellipse, mvtnorm, splines, stats, SNPchip, utils, lattice, ff, foreach, RcppEigen, matrixStats LinkingTo: preprocessCore (>= 1.17.7) Suggests: hapmapsnp6, genomewidesnp6Crlmm (>= 1.0.7), GGdata, snpStats, ellipse, RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: 6ab0d951372d6d328eaf2904b0c33971 NeedsCompilation: yes Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays. Description: Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms biocViews: Microarray, Preprocessing, SNP, Bioinformatics, CopyNumberVariants Author: Benilton S Carvalho, Robert Scharpf, Matt Ritchie, Ingo Ruczinski, Rafael A Irizarry Maintainer: Benilton S Carvalho , Robert Scharpf , Matt Ritchie source.ver: src/contrib/crlmm_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/crlmm_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/crlmm_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/crlmm_1.18.0.tgz vignettes: vignettes/crlmm/inst/doc/AffyGW.pdf, vignettes/crlmm/inst/doc/CopyNumberOverview.pdf, vignettes/crlmm/inst/doc/genotyping.pdf, vignettes/crlmm/inst/doc/gtypeDownstream.pdf, vignettes/crlmm/inst/doc/IlluminaPreprocessCN.pdf, vignettes/crlmm/inst/doc/Infrastructure.pdf vignetteTitles: Copy number estimation, Overview of copy number vignettes, crlmm Vignette - Genotyping, crlmm Vignette - Downstream Analysis, Preprocessing and genotyping Illumina arrays for copy number analysis, Infrastructure for copy number analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/crlmm/inst/doc/AffyGW.R, vignettes/crlmm/inst/doc/CopyNumberOverview.R, vignettes/crlmm/inst/doc/genotyping.R, vignettes/crlmm/inst/doc/gtypeDownstream.R, vignettes/crlmm/inst/doc/IlluminaPreprocessCN.R, vignettes/crlmm/inst/doc/Infrastructure.R suggestsMe: oligoClasses, SNPchip Package: CSAR Version: 1.12.0 Depends: R (>= 2.15.0), IRanges, GenomicRanges Imports: stats, utils Suggests: ShortRead, Biostrings License: Artistic-2.0 Archs: i386, x64 MD5sum: 06e96eb733efa053165218f55cf0b89d NeedsCompilation: yes Title: Statistical tools for the analysis of ChIP-seq data Description: Statistical tools for ChIP-seq data analysis. The package includes the statistical method described in Kaufmann et al. (2009) PLoS Biology: 7(4):e1000090. Briefly, Taking the average DNA fragment size subjected to sequencing into account, the software calculates genomic single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutation. biocViews: ChIPseq,Transcription,Genetics Author: Jose M Muino Maintainer: Jose M Muino source.ver: src/contrib/CSAR_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/CSAR_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/CSAR_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/CSAR_1.12.0.tgz vignettes: vignettes/CSAR/inst/doc/CSAR.pdf vignetteTitles: CSAR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CSAR/inst/doc/CSAR.R importsMe: NarrowPeaks suggestsMe: NarrowPeaks Package: ctc Version: 1.34.0 Depends: amap License: GPL-2 MD5sum: 087227114e8e83fa3973918991cc7e0e NeedsCompilation: no Title: Cluster and Tree Conversion. Description: Tools for export and import classification trees and clusters to other programs biocViews: Microarray, Clustering, Classification, DataImport, Visualization Author: Antoine Lucas , Laurent Gautier Maintainer: Antoine Lucas URL: http://antoinelucas.free.fr/ctc source.ver: src/contrib/ctc_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ctc_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ctc_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ctc_1.34.0.tgz vignettes: vignettes/ctc/inst/doc/ctc.pdf vignetteTitles: Introduction to ctc hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ctc/inst/doc/ctc.R Package: cummeRbund Version: 2.2.0 Depends: R (>= 2.7.0), BiocGenerics (>= 0.3.2), RSQLite, ggplot2, reshape2, fastcluster, rtracklayer, Gviz Imports: methods, plyr, BiocGenerics Suggests: cluster, plyr License: Artistic-2.0 MD5sum: 306ec32e43abaca32d13f97b8baa0f90 NeedsCompilation: no Title: Analysis, exploration, manipulation, and visualization of Cufflinks high-throughput sequencing data. Description: Allows for persistent storage, access, exploration, and manipulation of Cufflinks high-throughput sequencing data. In addition, provides numerous plotting functions for commonly used visualizations. biocViews: HighThroughputSequencing, HighThroughputSequencingData, RNAseq, RNAseqData, GeneExpression, DifferentialExpression, Infrastructure, DataImport, DataRepresentation, Visualization, Bioinformatics, Clustering, MultipleComparisons, QualityControl Author: L. Goff, C. Trapnell, D. Kelley Maintainer: Loyal A. Goff source.ver: src/contrib/cummeRbund_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cummeRbund_2.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cummeRbund_2.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cummeRbund_2.2.0.tgz vignettes: vignettes/cummeRbund/inst/doc/cuffData_schema.pdf, vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.pdf, vignettes/cummeRbund/inst/doc/cummeRbund-manual.pdf, vignettes/cummeRbund/inst/doc/ENCODE_SCV.pdf vignetteTitles: cuffData_schema.pdf, Sample cummeRbund workflow, CummeRbund User Guide, ENCODE_SCV.pdf hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.R, vignettes/cummeRbund/inst/doc/cummeRbund-manual.R suggestsMe: oneChannelGUI Package: cycle Version: 1.14.0 Depends: R (>= 2.10.0), Mfuzz Imports: Biobase, stats License: GPL-2 MD5sum: 1f279731175f46b358f9c500f8afb74b NeedsCompilation: no Title: Significance of periodic expression pattern in time-series data Description: Package for assessing the statistical significance of periodic expression based on Fourier analysis and comparison with data generated by different background models biocViews: Microarray, Bioinformatics,TimeCourse Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/cycle/index.html source.ver: src/contrib/cycle_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/cycle_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/cycle_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/cycle_1.14.0.tgz vignettes: vignettes/cycle/inst/doc/cycle.pdf vignetteTitles: Introduction to cycle hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cycle/inst/doc/cycle.R Package: daMA Version: 1.32.0 Imports: MASS, stats License: GPL (>= 2) MD5sum: e3aa3f26c370a815c0a7fd2baadef3f1 NeedsCompilation: no Title: Efficient design and analysis of factorial two-colour microarray data Description: This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data. Statistical details are described in Bretz et al. (2003, submitted) biocViews: Microarray, TwoChannel, Bioinformatics, DifferentialExpression Author: Jobst Landgrebe and Frank Bretz Maintainer: Jobst Landgrebe URL: http://www.microarrays.med.uni-goettingen.de source.ver: src/contrib/daMA_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/daMA_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/daMA_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/daMA_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: DART Version: 1.6.2 Depends: R (>= 2.10.0), igraph (>= 0.6.0) Suggests: breastCancerVDX, breastCancerMAINZ, Biobase License: GPL-2 MD5sum: 617c5648e286276c773db76a962ae56f NeedsCompilation: no Title: Denoising Algorithm based on Relevance network Topology Description: Denoising Algorithm based on Relevance network Topology (DART) is an algorithm designed to evaluate the consistency of prior information molecular signatures (e.g in-vitro perturbation expression signatures) in independent molecular data (e.g gene expression data sets). If consistent, a pruning network strategy is then used to infer the activation status of the molecular signature in individual samples. biocViews: GeneExpression, DifferentialExpression, GraphsAndNetworks, Pathways, Bioinformatics Author: Yan Jiao, Katherine Lawler, Andrew E Teschendorff Maintainer: Katherine Lawler source.ver: src/contrib/DART_1.6.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/DART_1.6.2.zip win64.binary.ver: bin/windows64/contrib/2.16/DART_1.6.2.zip mac.binary.ver: bin/macosx/contrib/2.16/DART_1.6.2.tgz vignettes: vignettes/DART/inst/doc/DART.pdf vignetteTitles: DART Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DART/inst/doc/DART.R Package: DASiR Version: 1.0.1 Depends: IRanges, GenomicRanges, XML, Biostrings License: LGPL (>= 3) MD5sum: cc70a9aef9735e84ef72176b39af9a69 NeedsCompilation: no Title: Distributed Annotation System in R Description: R package for programmatic retrieval of information from DAS servers biocViews: Annotation Author: Oscar Flores, Anna Mantsoki Maintainer: Oscar Flores , Anna Mantsoki source.ver: src/contrib/DASiR_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/DASiR_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/DASiR_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/DASiR_1.0.1.tgz vignettes: vignettes/DASiR/inst/doc/DASiR.pdf vignetteTitles: Programmatic retrieval of information from DAS servers hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DASiR/inst/doc/DASiR.R Package: DAVIDQuery Version: 1.20.0 Depends: RCurl (>= 1.4.0), utils License: GPL-2 MD5sum: 74f9b0d2dea8f8c3d075c2f0cf072c3d NeedsCompilation: no Title: Retrieval from the DAVID bioinformatics data resource into R Description: Tools to retrieve data from DAVID, the Database for Annotation, Visualization and Integrated Discovery biocViews: Annotation Author: Roger Day, Alex Lisovich Maintainer: Roger Day source.ver: src/contrib/DAVIDQuery_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DAVIDQuery_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DAVIDQuery_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DAVIDQuery_1.20.0.tgz vignettes: vignettes/DAVIDQuery/inst/doc/DAVIDQuery.pdf vignetteTitles: An R Package for retrieving data from DAVID into R objects. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DAVIDQuery/inst/doc/DAVIDQuery.R importsMe: IdMappingRetrieval Package: DBChIP Version: 1.4.0 Depends: R (>= 2.15.0), edgeR, DESeq Suggests: ShortRead, BiocGenerics License: GPL (>= 2) MD5sum: 74d2489e9440d06d1e59eb7622e091e7 NeedsCompilation: no Title: Differential Binding of Transcription Factor with ChIP-seq Description: DBChIP detects differentially bound sharp binding sites across multiple conditions, with or without matching control samples. biocViews: ChIPseq, Sequencing, Transcription, Genetics, Bioinformatics Author: Kun Liang Maintainer: Kun Liang source.ver: src/contrib/DBChIP_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DBChIP_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DBChIP_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DBChIP_1.4.0.tgz vignettes: vignettes/DBChIP/inst/doc/DBChIP.pdf vignetteTitles: DBChIP hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DBChIP/inst/doc/DBChIP.R Package: ddCt Version: 1.14.0 Depends: R (>= 2.3.0), Biobase (>= 1.10.0), RColorBrewer (>= 0.1-3), xtable, lattice, methods Suggests: RUnit License: LGPL-3 MD5sum: a05ae1fc3b8cd22aff2e195af63b6ff9 NeedsCompilation: no Title: The ddCt Algorithm for the Analysis of Quantitative Real-Time PCR (qRT-PCR) Description: The Delta-Delta-Ct (ddCt) Algorithm is an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. Compared to other approaches, it requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The ddCt package implements a pipeline to collect, analyse and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions. biocViews: GeneExpression, DifferentialExpression, MicrotitrePlateAssay, qPCR Author: Jitao David Zhang, Rudolf Biczok and Markus Ruschhaupt Maintainer: Jitao David Zhang source.ver: src/contrib/ddCt_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ddCt_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ddCt_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ddCt_1.14.0.tgz vignettes: vignettes/ddCt/inst/doc/rtPCR.pdf, vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.pdf, vignettes/ddCt/inst/doc/rtPCR-usage.pdf vignetteTitles: Introduction to the ddCt method for qRT-PCR data analysis: background,, algorithm and example, How to apply the ddCt method, Analyse RT-PCR data with the end-to-end script in ddCt package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ddCt/inst/doc/rtPCR.R, vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.R, vignettes/ddCt/inst/doc/rtPCR-usage.R Package: ddgraph Version: 1.4.0 Depends: graph, methods, Rcpp Imports: bnlearn (>= 2.8), gtools, pcalg, RColorBrewer, plotrix, MASS LinkingTo: Rcpp Suggests: testthat, Rgraphviz, e1071, ROCR, testthat License: GPL-3 Archs: i386, x64 MD5sum: 4492617a2668823d61ded01daf1a1965 NeedsCompilation: yes Title: Distinguish direct and indirect interactions with Graphical Modelling Description: Distinguish direct from indirect interactions in gene regulation and infer combinatorial code from highly correlated variables such as transcription factor binding profiles. The package implements the Neighbourhood Consistent PC algorithm (NCPC) and draws Direct Dependence Graphs to represent dependence structure around a target variable. The package also provides a unified interface to other Graphical Modelling (Bayesian Network) packages for distinguishing direct and indirect interactions. biocViews: Bioinformatics, GraphsAndNetworks Author: Robert Stojnic Maintainer: Robert Stojnic source.ver: src/contrib/ddgraph_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ddgraph_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ddgraph_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ddgraph_1.4.0.tgz vignettes: vignettes/ddgraph/inst/doc/ddgraph-cluster.pdf, vignettes/ddgraph/inst/doc/ddgraph-ddgraph-plot.pdf, vignettes/ddgraph/inst/doc/ddgraph.pdf vignetteTitles: ddgraph-cluster.pdf, ddgraph-ddgraph-plot.pdf, Overview of the 'ddgraph' package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ddgraph/inst/doc/ddgraph.R Package: DECIPHER Version: 1.6.0 Depends: R (>= 2.13.0), Biostrings (>= 2.16), RSQLite (>= 0.9), IRanges, stats Imports: Biostrings, RSQLite, IRanges, stats LinkingTo: Biostrings, RSQLite, IRanges, stats License: GPL-3 Archs: i386, x64 MD5sum: c091fa49ef452d58801c92e6079c46a0 NeedsCompilation: yes Title: Database Enabled Code for Ideal Probe Hybridization Employing R Description: A toolset that assist in the design of hybridization probes. biocViews: Clustering, Genetics, Sequencing, Infrastructure, DataImport, Visualization, Microarray, QualityControl Author: Erik Wright Maintainer: Erik Wright source.ver: src/contrib/DECIPHER_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DECIPHER_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DECIPHER_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DECIPHER_1.6.0.tgz vignettes: vignettes/DECIPHER/inst/doc/DECIPHERing.pdf, vignettes/DECIPHER/inst/doc/DesignPrimers.pdf, vignettes/DECIPHER/inst/doc/FindChimeras.pdf vignetteTitles: Getting Started DECIPHERing, Design Group-Specific Primers, Finding Chimeric Sequences hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DECIPHER/inst/doc/DECIPHERing.R, vignettes/DECIPHER/inst/doc/DesignPrimers.R, vignettes/DECIPHER/inst/doc/FindChimeras.R Package: DeconRNASeq Version: 1.2.0 Depends: R (>= 2.14.0), limSolve, pcaMethods, ggplot2, grid License: GPL-2 MD5sum: 248fab2e21e5cb1f05a12d4be765be76 NeedsCompilation: no Title: Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data Description: DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles. biocViews: Bioinformatics, ExperimentData, RNAExpressionData Author: Ting Gong Joseph D. Szustakowski Maintainer: Ting Gong source.ver: src/contrib/DeconRNASeq_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DeconRNASeq_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DeconRNASeq_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DeconRNASeq_1.2.0.tgz vignettes: vignettes/DeconRNASeq/inst/doc/DeconRNASeq.pdf vignetteTitles: DeconRNASeq Demo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DeconRNASeq/inst/doc/DeconRNASeq.R Package: DEDS Version: 1.34.0 Depends: R (>= 1.7.0) License: LGPL Archs: i386, x64 MD5sum: 41b6a1bc220f7951bf5c8fb45011e18c NeedsCompilation: yes Title: Differential Expression via Distance Summary for Microarray Data Description: This library contains functions that calculate various statistics of differential expression for microarray data, including t statistics, fold change, F statistics, SAM, moderated t and F statistics and B statistics. It also implements a new methodology called DEDS (Differential Expression via Distance Summary), which selects differentially expressed genes by integrating and summarizing a set of statistics using a weighted distance approach. biocViews: Bioinformatics, Microarray, DifferentialExpression Author: Yuanyuan Xiao , Jean Yee Hwa Yang . Maintainer: Yuanyuan Xiao source.ver: src/contrib/DEDS_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DEDS_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DEDS_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DEDS_1.34.0.tgz vignettes: vignettes/DEDS/inst/doc/DEDS.pdf vignetteTitles: DEDS.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEDS/inst/doc/DEDS.R Package: deepSNV Version: 1.6.0 Depends: R (>= 2.13.0), Rsamtools (>= 1.4.3), GenomicRanges, IRanges, Biostrings, VGAM, methods, graphics Imports: Rsamtools LinkingTo: Rsamtools License: GPL-3 Archs: i386, x64 MD5sum: 6fc1e1467d465bfd880db0dfdf700979 NeedsCompilation: yes Title: Detection of subclonal SNVs in deep sequencing experiments. Description: This package provides provides a quantitative variant caller for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. It assumes a comparative setup with a control experiment of the same loci and a beta-binomial model to discriminate sequencing errors and subclonal SNVs. biocViews: GeneticVariability, SNP, Sequencing, Genetics, DataImport Author: Moritz Gerstung and Niko Beerenwinkel Maintainer: Moritz Gerstung URL: http://www.cbg.ethz.ch/software/deepSNV source.ver: src/contrib/deepSNV_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/deepSNV_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/deepSNV_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/deepSNV_1.6.0.tgz vignettes: vignettes/deepSNV/inst/doc/deepSNV.pdf vignetteTitles: An R package for detecting low frequency variants in deep sequencing experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/deepSNV/inst/doc/deepSNV.R Package: DEGraph Version: 1.12.0 Depends: R (>= 2.10.0), R.utils Imports: graph, KEGGgraph, lattice, mvtnorm, R.methodsS3, RBGL, Rgraphviz, rrcov, NCIgraph Suggests: corpcor, fields, graph, KEGGgraph, lattice, marray, RBGL, rrcov, Rgraphviz, NCIgraph License: GPL-3 MD5sum: 4b7becb483223fa84661574b07890314 NeedsCompilation: no Title: Two-sample tests on a graph Description: DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions. This is to be contrasted with the more classical two-step approaches which first test individual genes, then test gene sets for enrichment in differentially expressed genes. These recent methods take into account the topology of the network to yield more powerful detection procedures. DEGraph provides methods to easily test all KEGG pathways for differential expression on any gene expression data set and tools to visualize the results. biocViews: Microarray, DifferentialExpression, GraphsAndNetworks, NetworkAnalysis, NetworkEnrichment Author: Laurent Jacob, Pierre Neuvial and Sandrine Dudoit Maintainer: Laurent Jacob source.ver: src/contrib/DEGraph_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DEGraph_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DEGraph_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DEGraph_1.12.0.tgz vignettes: vignettes/DEGraph/inst/doc/DEGraph.pdf vignetteTitles: DEGraph: differential expression testing for gene networks hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEGraph/inst/doc/DEGraph.R suggestsMe: graphite Package: DEGseq Version: 1.14.0 Depends: R (>= 2.8.0), qvalue, samr, methods Imports: graphics, grDevices, methods, stats, utils License: LGPL (>=2) Archs: i386, x64 MD5sum: e42729307543c2b044a84c91115e2347 NeedsCompilation: yes Title: Identify Differentially Expressed Genes from RNA-seq data Description: DEGseq is an R package to identify differentially expressed genes from RNA-Seq data. biocViews: RNAseq, Preprocessing, GeneExpression, DifferentialExpression Author: Likun Wang and Xi Wang . Maintainer: Likun Wang source.ver: src/contrib/DEGseq_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DEGseq_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DEGseq_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DEGseq_1.14.0.tgz vignettes: vignettes/DEGseq/inst/doc/DEGseq.pdf vignetteTitles: DEGseq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEGseq/inst/doc/DEGseq.R Package: deltaGseg Version: 1.0.3 Depends: R (>= 2.15.1), methods, ggplot2, changepoint, wavethresh, tseries, pvclust, fBasics, grid, reshape, scales Suggests: knitr License: GPL-2 MD5sum: 1cb4262c8c79b341054802d46b74f6f8 NeedsCompilation: no Title: deltaGseg Description: Identifying distinct subpopulations through multiscale time series analysis biocViews: Proteomics, TimeCourse, Visualization, Clustering Author: Diana Low, Efthymios Motakis Maintainer: Diana Low VignetteBuilder: knitr source.ver: src/contrib/deltaGseg_1.0.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/deltaGseg_1.0.3.zip win64.binary.ver: bin/windows64/contrib/2.16/deltaGseg_1.0.3.zip mac.binary.ver: bin/macosx/contrib/2.16/deltaGseg_1.0.3.tgz vignettes: vignettes/deltaGseg/inst/doc/deltaGseg.pdf vignetteTitles: deltaGseg hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/deltaGseg/inst/doc/deltaGseg.R Package: DESeq Version: 1.12.1 Depends: Biobase (>= 2.13.11), locfit, lattice Imports: genefilter, geneplotter, methods, MASS, RColorBrewer Suggests: pasilla (>= 0.2.10), vsn, gplots License: GPL (>= 3) Archs: i386, x64 MD5sum: 27d3828d1fb43206508892255a7ce6db NeedsCompilation: yes Title: Differential gene expression analysis based on the negative binomial distribution Description: Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution biocViews: HighThroughputSequencing, ChIPseq, RNAseq, SAGE, DifferentialExpression Author: Simon Anders, EMBL Heidelberg Maintainer: Simon Anders URL: http://www-huber.embl.de/users/anders/DESeq source.ver: src/contrib/DESeq_1.12.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/DESeq_1.12.1.zip win64.binary.ver: bin/windows64/contrib/2.16/DESeq_1.12.1.zip mac.binary.ver: bin/macosx/contrib/2.16/DESeq_1.12.1.tgz vignettes: vignettes/DESeq/inst/doc/DESeq.pdf, vignettes/DESeq/inst/doc/vst.pdf vignetteTitles: Analysing RNA-Seq data with the "DESeq" package, vst.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DESeq/inst/doc/DESeq.R dependsOnMe: DBChIP, easyRNASeq, SeqGSEA importsMe: ArrayExpressHTS, DiffBind, EDASeq, HTSFilter, rnaSeqMap suggestsMe: BitSeq, dexus, DiffBind, EDASeq, gCMAP, genefilter, GenomicRanges, oneChannelGUI, SSPA Package: DESeq2 Version: 1.0.19 Depends: GenomicRanges, IRanges, Biobase, lattice, Rcpp (>= 0.10.1), RcppArmadillo (>= 0.3.4.4) Imports: GenomicRanges, IRanges, Biobase, locfit, genefilter, methods, RColorBrewer, lattice LinkingTo: Rcpp, RcppArmadillo Suggests: parathyroidSE, pasilla (>= 0.2.10), vsn, gplots License: GPL (>= 3) Archs: i386, x64 MD5sum: 57d90679d87a4b03221a47a1042fe135 NeedsCompilation: yes Title: Differential gene expression analysis based on the negative binomial distribution Description: Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution biocViews: HighThroughputSequencing, ChIPseq, RNAseq, SAGE, DifferentialExpression Author: Michael Love (MPIMG Berlin), Simon Anders, Wolfgang Huber (EMBL Heidelberg) Maintainer: Michael Love source.ver: src/contrib/DESeq2_1.0.19.tar.gz win.binary.ver: bin/windows/contrib/2.16/DESeq2_1.0.19.zip win64.binary.ver: bin/windows64/contrib/2.16/DESeq2_1.0.19.zip mac.binary.ver: bin/macosx/contrib/2.16/DESeq2_1.0.19.tgz vignettes: vignettes/DESeq2/inst/doc/DESeq2.pdf, vignettes/DESeq2/inst/doc/vst.pdf vignetteTitles: Analyzing RNA-Seq data with the "DESeq2" package, vst.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DESeq2/inst/doc/DESeq2.R importsMe: HTSFilter Package: DEXSeq Version: 1.6.0 Depends: Biobase (>= 2.13.11) Imports: biomaRt, hwriter, methods, stringr, GenomicRanges, Rsamtools, statmod (>= 1.4.15) Suggests: GenomicFeatures, pasilla (>= 0.2.13), parathyroidSE Enhances: parallel License: GPL (>= 3) MD5sum: 568d00dc200126fa008fa9845e9f53a2 NeedsCompilation: no Title: Inference of differential exon usage in RNA-Seq Description: The package is focused on finding differential exon usage using RNA-seq exon counts between samples with different experimental designs. It provides functions that allows the user to make the necessary statistical tests based on a model that uses the negative binomial distribution to estimate the variance between biological replicates and generalized linear models for testing. The package also provides functions for the visualization and exploration of the results. biocViews: HighThroughputSequencing, RNAseq, DifferentialExpression Author: Simon Anders and Alejandro Reyes , both at EMBL Heidelberg Maintainer: Alejandro Reyes source.ver: src/contrib/DEXSeq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DEXSeq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DEXSeq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DEXSeq_1.6.0.tgz vignettes: vignettes/DEXSeq/inst/doc/DEXSeq.pdf vignetteTitles: Analyzing RNA-seq data for differential exon usage with the "DEXSeq" package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEXSeq/inst/doc/DEXSeq.R suggestsMe: GenomicRanges, oneChannelGUI Package: dexus Version: 1.0.2 Depends: R (>= 2.15), methods, BiocGenerics Suggests: parallel, statmod, stats, DESeq, RColorBrewer License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: 64e22a3c11f6890831141805d8786e38 NeedsCompilation: yes Title: DEXUS - Identifying Differential Expression in RNA-Seq Studies with Unknown Conditions or without Replicates Description: DEXUS identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. DEXUS works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. DEXUS does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power. biocViews: HighThroughputSequencing, Sequencing, Bioinformatics, Mus_musculus, Homo_sapiens, Zea_Mays, Macaca_mulatta, Pan_troglodytes, RNASeq, GeneExpression, DifferentialExpression, CellBiology, HighTroughputSequencingData, HapMap, RNAExpressionData, RNAseqData, Classification, QualityControl Author: Guenter Klambauer Maintainer: Guenter Klambauer source.ver: src/contrib/dexus_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/dexus_1.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/dexus_1.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/dexus_1.0.2.tgz vignettes: vignettes/dexus/inst/doc/dexus.pdf vignetteTitles: dexus: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dexus/inst/doc/dexus.R Package: DFP Version: 1.18.0 Depends: methods, Biobase (>= 2.5.5) License: GPL-2 MD5sum: 0b5feaaea66dcdaa2ccb601962d9d650 NeedsCompilation: no Title: Gene Selection Description: This package provides a supervised technique able to identify differentially expressed genes, based on the construction of \emph{Fuzzy Patterns} (FPs). The Fuzzy Patterns are built by means of applying 3 Membership Functions to discretized gene expression values. biocViews: Bioinformatics, Microarray, DifferentialExpression Author: R. Alvarez-Gonzalez, D. Glez-Pena, F. Diaz, F. Fdez-Riverola Maintainer: Rodrigo Alvarez-Glez source.ver: src/contrib/DFP_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DFP_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DFP_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DFP_1.18.0.tgz vignettes: vignettes/DFP/inst/doc/DFP.pdf vignetteTitles: Howto: Discriminat Fuzzy Pattern hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DFP/inst/doc/DFP.R Package: DiffBind Version: 1.6.2 Depends: R (>= 2.14.0), GenomicRanges Imports: RColorBrewer, amap, edgeR (>= 2.3.58), gplots, DESeq, grDevices, stats, utils, IRanges, zlibbioc LinkingTo: Rsamtools Suggests: DESeq, Rsamtools Enhances: rgl, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: a6fe456c04a3ab2a99a3743a6ddc0c25 NeedsCompilation: yes Title: Differential Binding Analysis of ChIP-Seq peak data Description: Compute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions. biocViews: Bioinformatics, HighThroughputSequencing, ChIPseq Author: Rory Stark , Gordon Brown Maintainer: Rory Stark source.ver: src/contrib/DiffBind_1.6.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/DiffBind_1.6.2.zip win64.binary.ver: bin/windows64/contrib/2.16/DiffBind_1.6.2.zip mac.binary.ver: bin/macosx/contrib/2.16/DiffBind_1.6.2.tgz vignettes: vignettes/DiffBind/inst/doc/DiffBind.pdf vignetteTitles: DiffBind User's Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DiffBind/inst/doc/DiffBind.R Package: diffGeneAnalysis Version: 1.42.0 Imports: graphics, grDevices, minpack.lm (>= 1.0-4), stats, utils License: GPL MD5sum: 0ba10e16cf39696debc89ca7c83780a9 NeedsCompilation: no Title: Performs differential gene expression Analysis Description: Analyze microarray data biocViews: Bioinformatics, Microarray, DifferentialExpression Author: Choudary Jagarlamudi Maintainer: Choudary Jagarlamudi source.ver: src/contrib/diffGeneAnalysis_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/diffGeneAnalysis_1.42.0.zip win64.binary.ver: bin/windows64/contrib/2.16/diffGeneAnalysis_1.42.0.zip mac.binary.ver: bin/macosx/contrib/2.16/diffGeneAnalysis_1.42.0.tgz vignettes: vignettes/diffGeneAnalysis/inst/doc/diffGeneAnalysis.pdf vignetteTitles: Documentation on diffGeneAnalysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/diffGeneAnalysis/inst/doc/diffGeneAnalysis.R Package: DirichletMultinomial Version: 1.2.0 Depends: IRanges Imports: stats4, methods Suggests: lattice, parallel, MASS, RColorBrewer, xtable License: LGPL-3 Archs: i386, x64 MD5sum: 401a7a3c08282eda564adb0e11f7fe8f NeedsCompilation: yes Title: Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data Description: Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial. biocViews: HighThroughputSequencing, Clustering, Classification Author: Martin Morgan Maintainer: Martin Morgan SystemRequirements: gsl source.ver: src/contrib/DirichletMultinomial_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DirichletMultinomial_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DirichletMultinomial_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DirichletMultinomial_1.2.0.tgz vignettes: vignettes/DirichletMultinomial/inst/doc/DirichletMultinomial.pdf vignetteTitles: An introduction to DirichletMultinomial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: dks Version: 1.6.0 Depends: R (>= 2.8) Imports: cubature License: GPL MD5sum: 6ca52eb34ba789e8ab2ba5a80180d415 NeedsCompilation: no Title: The double Kolmogorov-Smirnov package for evaluating multiple testing procedures. Description: The dks package consists of a set of diagnostic functions for multiple testing methods. The functions can be used to determine if the p-values produced by a multiple testing procedure are correct. These functions are designed to be applied to simulated data. The functions require the entire set of p-values from multiple simulated studies, so that the joint distribution can be evaluated. biocViews: Bioinformatics,MultipleComparisons,QualityControl Author: Jeffrey T. Leek Maintainer: Jeffrey T. Leek source.ver: src/contrib/dks_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/dks_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/dks_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/dks_1.6.0.tgz vignettes: vignettes/dks/inst/doc/betas2.pdf, vignettes/dks/inst/doc/dks.pdf vignetteTitles: betas2.pdf, dksTutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dks/inst/doc/dks.R Package: DNAcopy Version: 1.34.0 License: GPL (>= 2) Archs: i386, x64 MD5sum: 9a3b28df311e0e6c823ae497bede1cb9 NeedsCompilation: yes Title: DNA copy number data analysis Description: Segments DNA copy number data using circular binary segmentation to detect regions with abnormal copy number biocViews: Microarray, CopyNumberVariants Author: Venkatraman E. Seshan, Adam Olshen Maintainer: Venkatraman E. Seshan source.ver: src/contrib/DNAcopy_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DNAcopy_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DNAcopy_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DNAcopy_1.34.0.tgz vignettes: vignettes/DNAcopy/inst/doc/DNAcopy.pdf vignetteTitles: DNAcopy hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DNAcopy/inst/doc/DNAcopy.R dependsOnMe: CGHcall, cghMCR, Clonality, CNAnorm, CRImage, MEDIPS, snapCGH, SomatiCA importsMe: Clonality, cn.farms, GWASTools, MEDIPS, MinimumDistance, Repitools, snapCGH, SomatiCA suggestsMe: ADaCGH2, beadarraySNP, Clonality, cn.mops, fastseg, genoset, Repitools Package: domainsignatures Version: 1.20.0 Depends: R (>= 2.4.0), KEGG.db, prada, biomaRt, methods Imports: AnnotationDbi License: Artistic-2.0 MD5sum: b88866372f7f2a978bef088da87a4488 NeedsCompilation: no Title: Geneset enrichment based on InterPro domain signatures Description: Find significantly enriched gene classifications in a list of functionally undescribed genes based on their InterPro domain structure. biocViews: Annotation, Pathways, GeneSetEnrichment Author: Florian Hahne, Tim Beissbarth Maintainer: Florian Hahne source.ver: src/contrib/domainsignatures_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/domainsignatures_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/domainsignatures_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/domainsignatures_1.20.0.tgz vignettes: vignettes/domainsignatures/inst/doc/domainenrichment.pdf vignetteTitles: Gene set enrichment using InterPro domain signatures hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/domainsignatures/inst/doc/domainenrichment.R Package: DOSE Version: 1.6.0 Depends: R (>= 2.10), ggplot2 Imports: methods, plyr, qvalue, stats4, AnnotationDbi, DO.db, org.Hs.eg.db, igraph, scales, reshape2, graphics, GOSemSim Suggests: clusterProfiler, ReactomePA License: Artistic-2.0 MD5sum: 0e24acfd8588b9189df3a8e63266dc5c NeedsCompilation: no Title: Disease Ontology Semantic and Enrichment analysis Description: Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring DO semantic similarities, and hypergeometric test for enrichment analysis. biocViews: Bioinformatics, Annotation Author: Guangchuang Yu, Li-Gen Wang Maintainer: Guangchuang Yu source.ver: src/contrib/DOSE_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DOSE_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DOSE_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DOSE_1.6.0.tgz vignettes: vignettes/DOSE/inst/doc/DOSE.pdf vignetteTitles: An introduction to DOSE hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DOSE/inst/doc/DOSE.R dependsOnMe: ReactomePA importsMe: clusterProfiler suggestsMe: GOSemSim Package: DriverNet Version: 1.0.0 Depends: R (>= 2.10), methods License: GPL-3 MD5sum: 5171b8b6d44d672a7a045aae678b5e38 NeedsCompilation: no Title: Drivernet: uncovering somatic driver mutations modulating transcriptional networks in cancer Description: DriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values. Author: Ali Bashashati, Reza Haffari, Jiarui Ding, Gavin Ha, Kenneth Liu, Jamie Rosner and Sohrab Shah Maintainer: Jiarui Ding source.ver: src/contrib/DriverNet_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DriverNet_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DriverNet_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DriverNet_1.0.0.tgz vignettes: vignettes/DriverNet/inst/doc/DriverNet-Overview.pdf vignetteTitles: An introduction to DriverNet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DriverNet/inst/doc/DriverNet-Overview.R Package: DrugVsDisease Version: 2.0.0 Depends: R (>= 2.10), affy, limma, biomaRt, ArrayExpress, GEOquery, DrugVsDiseasedata, cMap2data, qvalue Imports: annotate, hgu133a.db, hgu133a2.db, hgu133plus2.db, RUnit, BiocGenerics, xtable License: GPL-3 MD5sum: 9f1efdcf92b49c9590326a817d7f4f32 NeedsCompilation: no Title: Comparison of disease and drug profiles using Gene set Enrichment Analysis Description: This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format. Author: C. Pacini Maintainer: j. Saez-Rodriguez source.ver: src/contrib/DrugVsDisease_2.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DrugVsDisease_2.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DrugVsDisease_2.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DrugVsDisease_2.0.0.tgz vignettes: vignettes/DrugVsDisease/inst/doc/DrugVsDisease.pdf vignetteTitles: DrugVsDisease hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DrugVsDisease/inst/doc/DrugVsDisease.R Package: DSS Version: 1.4.0 Depends: Biobase, locfdr Imports: methods License: GPL MD5sum: 6a97b49bf8d4a38fbe702b677cf1ac96 NeedsCompilation: no Title: Dispersion shrinakge for sequencing data. Description: DSS is an R library performing the differential expression analysis for RNA-seq count data. DSS implements a new dispersion shrinkage method to estimate the gene-specific biological variance. Extensive simulation results showed that DSS performs favorabily compared to DESeq and edgeR when the variation of biological variances is large. biocViews: HighThroughputSequencing, RNAseq, ChIPseq, DifferentialExpression Author: Hao Wu Maintainer: Hao Wu source.ver: src/contrib/DSS_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DSS_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DSS_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DSS_1.4.0.tgz vignettes: vignettes/DSS/inst/doc/DSS.pdf vignetteTitles: Differential expression for RNA-seq data with dispersion shrinkage hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DSS/inst/doc/DSS.R Package: DTA Version: 2.6.0 Depends: R (>= 2.10), LSD Imports: scatterplot3d License: Artistic-2.0 MD5sum: 5700affe36f7a4af86ad8ef821bfc115 NeedsCompilation: no Title: Dynamic Transcriptome Analysis Description: Dynamic Transcriptome Analysis (DTA) can monitor the cellular response to perturbations with higher sensitivity and temporal resolution than standard transcriptomics. The package implements the underlying kinetic modeling approach capable of the precise determination of synthesis- and decay rates from individual microarray or RNAseq measurements. biocViews: Microarray, DifferentialExpression, GeneExpression, Transcription Author: Bjoern Schwalb, Benedikt Zacher, Sebastian Duemcke, Achim Tresch Maintainer: Bjoern Schwalb source.ver: src/contrib/DTA_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DTA_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DTA_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DTA_2.6.0.tgz vignettes: vignettes/DTA/inst/doc/DTA.pdf vignetteTitles: A guide to Dynamic Transcriptome Analysis (DTA) hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DTA/inst/doc/DTA.R Package: dualKS Version: 1.20.0 Depends: R (>= 2.6.0), Biobase (>= 1.15.0), affy, methods License: LGPL (>= 2.0) MD5sum: 678ae5e26ec9195d462998bf2666f5ec NeedsCompilation: no Title: Dual KS Discriminant Analysis and Classification Description: This package implements a Kolmogorov Smirnov rank-sum based algorithm for training (i.e. discriminant analysis--identification of genes that discriminate between classes) and classification of gene expression data sets. One of the chief strengths of this approach is that it is amenable to the "multiclass" problem. That is, it can discriminate between more than 2 classes. biocViews: Microarray, Bioinformatics Author: Eric J. Kort, Yarong Yang Maintainer: Yarong Yang source.ver: src/contrib/dualKS_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/dualKS_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/dualKS_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/dualKS_1.20.0.tgz vignettes: vignettes/dualKS/inst/doc/dualKS.pdf vignetteTitles: dualKS.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dualKS/inst/doc/dualKS.R Package: dyebias Version: 1.18.0 Depends: R (>= 1.4.1), marray, Biobase Suggests: limma, convert, GEOquery, dyebiasexamples, methods License: GPL-3 MD5sum: 34ed13529d06f82ff1625162dcc80408 NeedsCompilation: no Title: The GASSCO method for correcting for slide-dependent gene-specific dye bias Description: Many two-colour hybridizations suffer from a dye bias that is both gene-specific and slide-specific. The former depends on the content of the nucleotide used for labeling; the latter depends on the labeling percentage. The slide-dependency was hitherto not recognized, and made addressing the artefact impossible. Given a reasonable number of dye-swapped pairs of hybridizations, or of same vs. same hybridizations, both the gene- and slide-biases can be estimated and corrected using the GASSCO method (Margaritis et al., Mol. Sys. Biol. 5:266 (2009), doi:10.1038/msb.2009.21) biocViews: Microarray, TwoChannel, QualityControl, Preprocessing Author: Philip Lijnzaad and Thanasis Margaritis Maintainer: Philip Lijnzaad URL: http://www.holstegelab.nl/publications/margaritis_lijnzaad source.ver: src/contrib/dyebias_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/dyebias_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/dyebias_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/dyebias_1.18.0.tgz vignettes: vignettes/dyebias/inst/doc/dyebiasCompleteVignette.pdf, vignettes/dyebias/inst/doc/dyebias-vignette.pdf, vignettes/dyebias/inst/doc/gassco.pdf vignetteTitles: dyebiasCompleteVignette.pdf, dye bias correction, gassco.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/dyebias/inst/doc/dyebias-vignette.R Package: DynDoc Version: 1.38.0 Depends: methods, utils Imports: methods License: Artistic-2.0 MD5sum: 57cb979e7f4a3ffa6efe0c8844ae2d8e NeedsCompilation: no Title: Dynamic document tools Description: A set of functions to create and interact with dynamic documents and vignettes. biocViews: ReportWriting, Infrastructure Author: R. Gentleman, Jeff Gentry Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/DynDoc_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/DynDoc_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/DynDoc_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/DynDoc_1.38.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: tkWidgets Package: EasyqpcR Version: 1.2.0 Imports: plyr, matrixStats, plotrix, gWidgetsRGtk2 Suggests: SLqPCR, qpcrNorm, qpcR, knitr License: GPL (>=2) MD5sum: bf824722cb5430b722fc9be3390a0902 NeedsCompilation: no Title: EasyqpcR for low-throughput real-time quantitative PCR data analysis Description: This package is based on the qBase algorithms published by Hellemans et al. in 2007. The EasyqpcR package allows you to import easily qPCR data files as described in the vignette. Thereafter, you can calculate amplification efficiencies, relative quantities and their standard errors, normalization factors based on the best reference genes choosen (using the SLqPCR package), and then the normalized relative quantities, the NRQs scaled to your control and their standard errors. This package has been created for low-throughput qPCR data analysis. biocViews: qPCR, GeneExpression Author: Le Pape Sylvain Maintainer: Le Pape Sylvain source.ver: src/contrib/EasyqpcR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/EasyqpcR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/EasyqpcR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/EasyqpcR_1.2.0.tgz vignettes: vignettes/EasyqpcR/inst/doc/vignette_EasyqpcR.pdf vignetteTitles: EasyqpcR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EasyqpcR/inst/doc/vignette_EasyqpcR.R Package: easyRNASeq Version: 1.6.4 Depends: graphics, methods, parallel, utils, genomeIntervals (>= 1.16.0), Biobase (>= 2.20.1), BiocGenerics (>= 0.6.0), biomaRt (>= 2.16.0), edgeR (>= 3.2.4), Biostrings (>= 2.28.0), BSgenome (>= 1.28.0), DESeq (>= 1.12.1), GenomicRanges (>= 1.12.5), IRanges (>= 1.18.4), LSD (>= 2.5), Rsamtools (>= 1.12.4), ShortRead (>= 1.18.0) Suggests: BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.17), GenomicFeatures (>= 1.11.0), RnaSeqTutorial (>= 0.0.11) Enhances: edgeR, genomeIntervals, DESeq, ShortRead License: Artistic-2.0 MD5sum: 610122343542e581218286c2d0782a50 NeedsCompilation: no Title: Count summarization and normalization for RNA-Seq data. Description: Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package. biocViews: GeneExpression, RNAseq, Genetics, Preprocessing Author: Nicolas Delhomme, Ismael Padioleau Maintainer: Nicolas Delhomme source.ver: src/contrib/easyRNASeq_1.6.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/easyRNASeq_1.6.4.zip win64.binary.ver: bin/windows64/contrib/2.16/easyRNASeq_1.6.4.zip mac.binary.ver: bin/macosx/contrib/2.16/easyRNASeq_1.6.4.tgz vignettes: vignettes/easyRNASeq/inst/doc/easyRNASeq.pdf vignetteTitles: RNA-Seq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/easyRNASeq/inst/doc/easyRNASeq.R Package: EBarrays Version: 2.24.0 Depends: R (>= 1.8.0), Biobase, lattice, methods Imports: Biobase, cluster, graphics, grDevices, lattice, methods, stats License: GPL (>= 2) Archs: i386, x64 MD5sum: 93ffaa72f59fe3013146279b4730d7e2 NeedsCompilation: yes Title: Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification Description: EBarrays provides tools for the analysis of replicated/unreplicated microarray data. biocViews: Clustering, DifferentialExpression Author: Ming Yuan, Michael Newton, Deepayan Sarkar and Christina Kendziorski Maintainer: Ming Yuan source.ver: src/contrib/EBarrays_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/EBarrays_2.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/EBarrays_2.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/EBarrays_2.24.0.tgz vignettes: vignettes/EBarrays/inst/doc/vignette.pdf vignetteTitles: Introduction to EBarrays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBarrays/inst/doc/vignette.R dependsOnMe: EBcoexpress, gaga, geNetClassifier suggestsMe: Category Package: EBcoexpress Version: 1.4.0 Depends: EBarrays, mclust, minqa Suggests: graph, igraph, colorspace License: GPL (>= 2) Archs: i386, x64 MD5sum: 8aa07723163fec6861ff69fff5177869 NeedsCompilation: yes Title: EBcoexpress for Differential Co-Expression Analysis Description: An Empirical Bayesian Approach to Differential Co-Expression Analysis at the Gene-Pair Level Author: John A. Dawson Maintainer: John A. Dawson source.ver: src/contrib/EBcoexpress_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/EBcoexpress_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/EBcoexpress_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/EBcoexpress_1.4.0.tgz vignettes: vignettes/EBcoexpress/inst/doc/EBcoexpressVignette.pdf vignetteTitles: EBcoexpress Demo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBcoexpress/inst/doc/EBcoexpressVignette.R Package: EBImage Version: 4.2.1 Imports: methods, graphics, stats, abind, utils, tiff, jpeg, png, locfit License: LGPL Archs: i386, x64 MD5sum: 72cf5f7aa0092a5e35d700f0ee071329 NeedsCompilation: yes Title: Image processing toolbox for R Description: EBImage is an R package which provides general purpose functionality for the reading, writing, processing and analysis of images. Furthermore, in the context of microscopy based cellular assays, EBImage offers tools to transform the images, segment cells and extract quantitative cellular descriptors. biocViews: Visualization Author: Gregoire Pau, Andrzej Oles, Mike Smith, Oleg Sklyar, Wolfgang Huber Maintainer: Andrzej Oles source.ver: src/contrib/EBImage_4.2.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/EBImage_4.2.1.zip win64.binary.ver: bin/windows64/contrib/2.16/EBImage_4.2.1.zip mac.binary.ver: bin/macosx/contrib/2.16/EBImage_4.2.1.tgz vignettes: vignettes/EBImage/inst/doc/EBImage-introduction.pdf vignetteTitles: Introduction to EBImage hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBImage/inst/doc/EBImage-introduction.R dependsOnMe: CRImage, imageHTS suggestsMe: HilbertVis Package: ecolitk Version: 1.32.0 Depends: R (>= 2.10) Imports: Biobase, graphics, methods Suggests: ecoliLeucine, ecolicdf, graph, multtest, affy License: GPL (>= 2) MD5sum: ff13606dce31aeb0b7c404a3f8390589 NeedsCompilation: no Title: Meta-data and tools for E. coli Description: Meta-data and tools to work with E. coli. The tools are mostly plotting functions to work with circular genomes. They can used with other genomes/plasmids. biocViews: Annotation, Visualization Author: Laurent Gautier Maintainer: Laurent Gautier source.ver: src/contrib/ecolitk_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ecolitk_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ecolitk_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ecolitk_1.32.0.tgz vignettes: vignettes/ecolitk/inst/doc/ecolitk.pdf vignetteTitles: ecolitk hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ecolitk/inst/doc/ecolitk.R Package: EDASeq Version: 1.6.0 Depends: BiocGenerics (>= 0.1.3), Biobase (>= 2.15.1), ShortRead (>= 1.11.42), Rsamtools (>= 1.5.75), aroma.light Imports: methods, graphics, BiocGenerics, IRanges (>= 1.13.9), DESeq Suggests: yeastRNASeq, leeBamViews, edgeR, DESeq License: Artistic-2.0 MD5sum: 7b4485e03361b7b92453ffb992e1a730 NeedsCompilation: no Title: Exploratory Data Analysis and Normalization for RNA-Seq Description: Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010). biocViews: HighThroughputSequencing, RNAseq, Preprocessing, QualityControl, DifferentialExpression Author: Davide Risso and Sandrine Dudoit Maintainer: Davide Risso source.ver: src/contrib/EDASeq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/EDASeq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/EDASeq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/EDASeq_1.6.0.tgz vignettes: vignettes/EDASeq/inst/doc/EDASeq.pdf vignetteTitles: EDASeq: Exploratory Data Analysis and Normalization for RNA-Seq data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EDASeq/inst/doc/EDASeq.R suggestsMe: HTSFilter, oneChannelGUI Package: edgeR Version: 3.2.4 Depends: R (>= 2.15.0), methods, limma Suggests: MASS, statmod, splines, locfit, KernSmooth License: GPL (>=2) Archs: i386, x64 MD5sum: f3781187ab1b5974ed2400eb542cf127 NeedsCompilation: yes Title: Empirical analysis of digital gene expression data in R Description: Differential expression analysis of RNA-seq and digital gene expression profiles with biological replication. Uses empirical Bayes estimation and exact tests based on the negative binomial distribution. Also useful for differential signal analysis with other types of genome-scale count data. biocViews: Bioinformatics, DifferentialExpression, SAGE, HighThroughputSequencing, RNAseq, ChIPseq Author: Mark Robinson , Davis McCarthy , Yunshun Chen , Aaron Lun , Gordon Smyth Maintainer: Mark Robinson , Davis McCarthy , Yunshun Chen , Gordon Smyth source.ver: src/contrib/edgeR_3.2.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/edgeR_3.2.4.zip win64.binary.ver: bin/windows64/contrib/2.16/edgeR_3.2.4.zip mac.binary.ver: bin/macosx/contrib/2.16/edgeR_3.2.4.tgz vignettes: vignettes/edgeR/inst/doc/edgeR.pdf, vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf vignetteTitles: edgeR Vignette, edgeRUsersGuide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/edgeR/inst/doc/edgeR.R dependsOnMe: DBChIP, easyRNASeq, manta importsMe: ArrayExpressHTS, DiffBind, HTSFilter, MEDIPS, Repitools, rnaSeqMap, tweeDEseq suggestsMe: baySeq, BitSeq, cqn, EDASeq, GenomicRanges, goseq, GSVA, oneChannelGUI, Repitools, SSPA Package: eiR Version: 1.0.3 Depends: R (>= 2.10.0), ChemmineR (>= 2.11.18), methods Imports: snow, tools, snowfall, RUnit, methods,ChemmineR,RCurl,digest, BiocGenerics Suggests: RCurl,snow License: Artistic-2.0 MD5sum: 745a6c6f905db94e135c5c3ae9b86711 NeedsCompilation: yes Title: Accelerated similarity searching of small molecules Description: The eiR package provides utilities for accelerated structure similarity searching of very large small molecule data sets using an embedding and indexing approach. biocViews: Infrastructure, DataImport, Clustering, Bioinformatics, Proteomics Author: Kevin Horan Maintainer: Kevin Horan source.ver: src/contrib/eiR_1.0.3.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/eiR_1.0.3.tgz vignettes: vignettes/eiR/inst/doc/eiR.pdf vignetteTitles: eiR hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/eiR/inst/doc/eiR.R Package: eisa Version: 1.12.2 Depends: isa2, Biobase (>= 2.17.8), AnnotationDbi, methods Imports: BiocGenerics, Category, genefilter, DBI Suggests: igraph (>= 0.6), Matrix, GOstats, GO.db, KEGG.db, biclust, MASS, xtable, ALL, hgu95av2.db, targetscan.Hs.eg.db, org.Hs.eg.db License: GPL (>= 2) MD5sum: cf72f15b8f6755974ae9165c865bd69c NeedsCompilation: no Title: Expression data analysis via the Iterative Signature Algorithm Description: The Iterative Signature Algorithm (ISA) is a biclustering method; it finds correlated blocks (transcription modules) in gene expression (or other tabular) data. The ISA is capable of finding overlapping modules and it is resilient to noise. This package provides a convenient interface to the ISA, using standard BioConductor data structures; and also contains various visualization tools that can be used with other biclustering algorithms. biocViews: Classification, Visualization, Microarray, GeneExpression Author: Gabor Csardi Maintainer: Gabor Csardi source.ver: src/contrib/eisa_1.12.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/eisa_1.12.2.zip win64.binary.ver: bin/windows64/contrib/2.16/eisa_1.12.2.zip mac.binary.ver: bin/macosx/contrib/2.16/eisa_1.12.2.tgz vignettes: vignettes/eisa/inst/doc/EISA_biclust.pdf, vignettes/eisa/inst/doc/EISA_tutorial.pdf, vignettes/eisa/inst/doc/ISA_internals.pdf, vignettes/eisa/inst/doc/tissues.pdf vignetteTitles: The eisa and the biclust packages, The Iterative Signature Algorithm for Gene Expression Data, ISA_internals.pdf, tissues.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/eisa/inst/doc/EISA_biclust.R, vignettes/eisa/inst/doc/EISA_tutorial.R dependsOnMe: ExpressionView importsMe: ExpressionView Package: ensemblVEP Version: 1.0.5 Depends: methods, BiocGenerics, GenomicRanges, VariantAnnotation Imports: Biostrings, IRanges Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: d042fc0ebe9cd846cf0a44e5cf3f38a6 NeedsCompilation: no Title: R Interface to Ensembl Variant Effect Predictor Description: Query the Ensembl Variant Effect Predictor via the perl API biocViews: Annotation, Bioinformatics Author: Valerie Obenchain , Maintainer: Valerie Obenchain SystemRequirements: Ensembl VEP (API version 73) and the Perl package DBD::mysql must be installed. See the package README and Ensembl web site, http://www.ensembl.org/info/docs/variation/vep/index.html for installation instructions. source.ver: src/contrib/ensemblVEP_1.0.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/ensemblVEP_1.0.5.zip win64.binary.ver: bin/windows64/contrib/2.16/ensemblVEP_1.0.5.zip mac.binary.ver: bin/macosx/contrib/2.16/ensemblVEP_1.0.5.tgz vignettes: vignettes/ensemblVEP/inst/doc/ensemblVEP.pdf vignetteTitles: ensemblVEP hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ensemblVEP/inst/doc/ensemblVEP.R Package: ENVISIONQuery Version: 1.8.1 Depends: rJava, XML, utils License: GPL-2 MD5sum: 45123a095a13220909ff8e5f934e6670 NeedsCompilation: no Title: Retrieval from the ENVISION bioinformatics data portal into R Description: Tools to retrieve data from ENVISION, the Database for Annotation, Visualization and Integrated Discovery portal biocViews: Annotation Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/ENVISIONQuery_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/ENVISIONQuery_1.8.1.zip win64.binary.ver: bin/windows64/contrib/2.16/ENVISIONQuery_1.8.1.zip mac.binary.ver: bin/macosx/contrib/2.16/ENVISIONQuery_1.8.1.tgz vignettes: vignettes/ENVISIONQuery/inst/doc/ENVISIONQuery.pdf vignetteTitles: An R Package for retrieving data from EnVision into R objects. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ENVISIONQuery/inst/doc/ENVISIONQuery.R dependsOnMe: IdMappingRetrieval importsMe: IdMappingRetrieval Package: epigenomix Version: 1.0.1 Depends: R (>= 2.12.0), methods, Biobase, IRanges, GenomicRanges Imports: methods, BiocGenerics, Biobase, IRanges, GenomicRanges, beadarray License: LGPL-3 MD5sum: 46cabc92b926fcc984a19f1f83525b35 NeedsCompilation: no Title: Epigenetic and gene expression data normalization and integration with mixture models Description: A package for the integrative analysis of microarray based gene expression and histone modification data obtained by ChIP-seq. The package provides methods for data preprocessing and matching as well as methods for fitting bayesian mixture models in order to detect genes with differences in both data types. biocViews: ChIPseq, GeneExpression, DifferentialExpression, Classification Author: Hans-Ulrich Klein, Martin Schaefer Maintainer: Hans-Ulrich Klein source.ver: src/contrib/epigenomix_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/epigenomix_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/epigenomix_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/epigenomix_1.0.1.tgz vignettes: vignettes/epigenomix/inst/doc/epigenomix.pdf vignetteTitles: epigenomix package vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/epigenomix/inst/doc/epigenomix.R Package: ExiMiR Version: 2.2.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), affy (>= 1.26.1), limma Imports: affyio(>= 1.13.3), Biobase(>= 2.5.5), preprocessCore(>= 1.10.0) License: GPL-2 MD5sum: 0f9baf4ca8088395b73f56b7ef1db103 NeedsCompilation: no Title: R functions for the normalization of Exiqon miRNA array data Description: This package contains functions for reading raw data in ImaGene TXT format obtained from Exiqon miRCURY LNA arrays, annotating them with appropriate GAL files, and normalizing them using a spike-in probe-based method. Other platforms and data formats are also supported. biocViews: Microarray, OneChannel, DualChannel, Preprocessing, GeneExpression, Transcription Author: Sylvain Gubian , Alain Sewer , PMP SA Maintainer: Sylvain Gubian source.ver: src/contrib/ExiMiR_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ExiMiR_2.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ExiMiR_2.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ExiMiR_2.2.0.tgz vignettes: vignettes/ExiMiR/inst/doc/ExiMiR-vignette.pdf vignetteTitles: Description of ExiMiR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ExiMiR/inst/doc/ExiMiR-vignette.R Package: exomeCopy Version: 1.6.0 Depends: IRanges, GenomicRanges, Rsamtools Imports: stats4, methods Suggests: Biostrings License: GPL (>= 2) Archs: i386, x64 MD5sum: 946ef93fc133af2115fcbc4dcce3c95c NeedsCompilation: yes Title: Copy number variant detection from exome sequencing read depth Description: Detection of copy number variants (CNV) from exome sequencing samples, including unpaired samples. The package implements a hidden Markov model which uses positional covariates, such as background read depth and GC-content, to simultaneously normalize and segment the samples into regions of constant copy count. biocViews: CopyNumberVariants, Sequencing, HighThroughputSequencing, Genetics Author: Michael Love Maintainer: Michael Love source.ver: src/contrib/exomeCopy_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/exomeCopy_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/exomeCopy_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/exomeCopy_1.6.0.tgz vignettes: vignettes/exomeCopy/inst/doc/exomeCopy.pdf vignetteTitles: Copy number variant detection in exome sequencing data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/exomeCopy/inst/doc/exomeCopy.R Package: explorase Version: 1.24.0 Depends: R (>= 2.6.2) Imports: limma, rggobi, RGtk2 Suggests: cairoDevice License: GPL-2 MD5sum: 1625a6b7d9973ea4695ebe5992192170 NeedsCompilation: no Title: GUI for exploratory data analysis of systems biology data Description: explore and analyze *omics data with R and GGobi biocViews: Visualization,Microarray,GUI Author: Michael Lawrence, Eun-kyung Lee, Dianne Cook, Jihong Kim, Hogeun An, and Dongshin Kim Maintainer: Michael Lawrence URL: http://www.metnetdb.org/MetNet_exploRase.htm source.ver: src/contrib/explorase_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/explorase_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/explorase_1.24.0.zip vignettes: vignettes/explorase/inst/doc/explorase.pdf vignetteTitles: Introduction to exploRase hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/explorase/inst/doc/explorase.R Package: ExpressionView Version: 1.12.0 Depends: caTools, bitops, methods, isa2, eisa, GO.db, KEGG.db, AnnotationDbi Imports: methods, isa2, eisa, GO.db, KEGG.db, AnnotationDbi Suggests: ALL, hgu95av2.db, biclust, affy License: GPL (>= 2) Archs: i386, x64 MD5sum: 1abeacb20057fe8739a6dcf9858f6967 NeedsCompilation: yes Title: Visualize biclusters identified in gene expression data Description: ExpressionView visualizes possibly overlapping biclusters in a gene expression matrix. It can use the result of the ISA method (eisa package) or the algorithms in the biclust package or others. The viewer itself was developed using Adobe Flex and runs in a flash-enabled web browser. biocViews: Classification, Visualization, Microarray, GeneExpression Author: Andreas Luscher Maintainer: Gabor Csardi source.ver: src/contrib/ExpressionView_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ExpressionView_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ExpressionView_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ExpressionView_1.12.0.tgz vignettes: vignettes/ExpressionView/inst/doc/ExpressionView.format.pdf, vignettes/ExpressionView/inst/doc/ExpressionView.ordering.pdf, vignettes/ExpressionView/inst/doc/ExpressionView.tutorial.pdf vignetteTitles: ExpressionView file format, How the ordering algorithm works, ExpressionView hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ExpressionView/inst/doc/ExpressionView.format.R, vignettes/ExpressionView/inst/doc/ExpressionView.ordering.R, vignettes/ExpressionView/inst/doc/ExpressionView.tutorial.R Package: externalVector Version: 1.26.0 Depends: R (>= 1.8.0), methods, stats License: LGPL Archs: i386, x64 MD5sum: 74cfedcca3096e91b62dd7792e301227 NeedsCompilation: yes Title: Vector objects for R with external storage Description: Basic class definitions and generics for external pointer based vector objects for R. A simple in-memory implementation is also provided. biocViews: Infrastructure Author: Saikat DebRoy Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/externalVector_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/externalVector_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/externalVector_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/externalVector_1.26.0.tgz hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: fabia Version: 2.6.2 Depends: R (>= 2.8.0), Biobase Imports: methods, graphics, grDevices, stats, utils License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: 18ef22bcee36eb19e1680ed2ac0d369c NeedsCompilation: yes Title: FABIA: Factor Analysis for Bicluster Acquisition Description: Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C. biocViews: Bioinformatics, Statistics, Microarray, DifferentialExpression, MultipleComparisons, Clustering, Visualization Author: Sepp Hochreiter Maintainer: Sepp Hochreiter URL: http://www.bioinf.jku.at/software/fabia/fabia.html source.ver: src/contrib/fabia_2.6.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/fabia_2.6.2.zip win64.binary.ver: bin/windows64/contrib/2.16/fabia_2.6.2.zip mac.binary.ver: bin/macosx/contrib/2.16/fabia_2.6.2.tgz vignettes: vignettes/fabia/inst/doc/fabia.pdf vignetteTitles: FABIA: Manual for the R package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fabia/inst/doc/fabia.R dependsOnMe: hapFabia Package: factDesign Version: 1.36.0 Depends: Biobase (>= 2.5.5) Imports: stats Suggests: affy, genefilter, multtest License: LGPL MD5sum: 411eef256f0203f3717c867eb643a59e NeedsCompilation: no Title: Factorial designed microarray experiment analysis Description: This package provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection. biocViews: Bioinformatics, Microarray, DifferentialExpression Author: Denise Scholtens Maintainer: Denise Scholtens source.ver: src/contrib/factDesign_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/factDesign_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/factDesign_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/factDesign_1.36.0.tgz vignettes: vignettes/factDesign/inst/doc/factDesign.pdf vignetteTitles: factDesign hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/factDesign/inst/doc/factDesign.R Package: farms Version: 1.12.0 Depends: R (>= 2.8), affy (>= 1.20.0), MASS, methods Imports: affy, MASS, Biobase (>= 1.13.41), methods, graphics Suggests: affydata, Biobase, utils License: LGPL (>= 2.1) MD5sum: 890da21c88cb551788ce0fe4222896a9 NeedsCompilation: no Title: FARMS - Factor Analysis for Robust Microarray Summarization Description: The package provides the summarization algorithm called Factor Analysis for Robust Microarray Summarization (FARMS) and a novel unsupervised feature selection criterion called "I/NI-calls" biocViews: GeneExpression, Microarray, Preprocessing, QualityControl Author: Djork-Arne Clevert Maintainer: Djork-Arne Clevert URL: http://www.bioinf.jku.at/software/farms/farms.html source.ver: src/contrib/farms_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/farms_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/farms_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/farms_1.12.0.tgz vignettes: vignettes/farms/inst/doc/farms.pdf vignetteTitles: Using farms hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/farms/inst/doc/farms.R Package: fastseg Version: 1.6.0 Depends: R (>= 2.13), GenomicRanges, Biobase Imports: graphics, stats, IRanges, BiocGenerics Suggests: DNAcopy, oligo License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: 2695d83884d8a6365b2256ffd616c49d NeedsCompilation: yes Title: fastseg - a fast segmentation algorithm Description: fastseg implements a very fast and efficient segmentation algorithm. It has similar functionality as DNACopy (Olshen and Venkatraman 2004), but is considerably faster and more flexible. fastseg can segment data from DNA microarrays and data from next generation sequencing for example to detect copy number segments. Further it can segment data from RNA microarrays like tiling arrays to identify transcripts. Most generally, it can segment data given as a matrix or as a vector. Various data formats can be used as input to fastseg like expression set objects for microarrays or GRanges for sequencing data. The segmentation criterion of fastseg is based on a statistical test in a Bayesian framework, namely the cyber t-test (Baldi 2001). The speed-up arises from the facts, that sampling is not necessary in for fastseg and that a dynamic programming approach is used for calculation of the segments' first and higher order moments. biocViews: Classification, CopyNumberVariants Author: Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/fastseg/fastseg.html source.ver: src/contrib/fastseg_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/fastseg_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/fastseg_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/fastseg_1.6.0.tgz vignettes: vignettes/fastseg/inst/doc/fastseg.pdf vignetteTitles: fastseg: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fastseg/inst/doc/fastseg.R Package: fdrame Version: 1.32.0 Imports: tcltk, graphics, grDevices, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 477c66983b6d3c626cd79b8514c04d6a NeedsCompilation: yes Title: FDR adjustments of Microarray Experiments (FDR-AME) Description: This package contains two main functions. The first is fdr.ma which takes normalized expression data array, experimental design and computes adjusted p-values It returns the fdr adjusted p-values and plots, according to the methods described in (Reiner, Yekutieli and Benjamini 2002). The second, is fdr.gui() which creates a simple graphic user interface to access fdr.ma biocViews: Microarray,DifferentialExpression,MultipleComparisons Author: Yoav Benjamini, Effi Kenigsberg, Anat Reiner, Daniel Yekutieli Maintainer: Effi Kenigsberg source.ver: src/contrib/fdrame_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/fdrame_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/fdrame_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/fdrame_1.32.0.tgz vignettes: vignettes/fdrame/inst/doc/fdrame.pdf vignetteTitles: Annotation Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fdrame/inst/doc/fdrame.R Package: ffpe Version: 1.4.0 Depends: R (>= 2.10.0), TTR, methods Imports: Biobase, BiocGenerics, affy, lumi, methylumi, sfsmisc Suggests: genefilter, affy, ffpeExampleData License: GPL (>2) MD5sum: 2a9e0eb4ae93d2e03d0f22da6d64c217 NeedsCompilation: no Title: Quality assessment and control for FFPE microarray expression data Description: Identify low-quality data using metrics developed for expression data derived from Formalin-Fixed, Paraffin-Embedded (FFPE) data. Also a function for making Concordance at the Top plots (CAT-plots). biocViews: Microarray, GeneExpression, QualityControl, Bioinformatics Author: Levi Waldron Maintainer: Levi Waldron source.ver: src/contrib/ffpe_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ffpe_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ffpe_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ffpe_1.4.0.tgz vignettes: vignettes/ffpe/inst/doc/ffpe.pdf vignetteTitles: ffpe package user guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ffpe/inst/doc/ffpe.R Package: flagme Version: 1.16.2 Depends: gcspikelite, xcms Imports: gplots, graphics, MASS, methods, SparseM, stats, utils License: LGPL (>= 2) Archs: i386, x64 MD5sum: 5cfd429768633f64f0c2252bb2a90b57 NeedsCompilation: yes Title: Analysis of Metabolomics GC/MS Data Description: Fragment-level analysis of gas chromatography - mass spectrometry metabolomics data biocViews: Bioinformatics, DifferentialExpression, MassSpectrometry Author: Mark Robinson Maintainer: Mark Robinson source.ver: src/contrib/flagme_1.16.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/flagme_1.16.2.zip win64.binary.ver: bin/windows64/contrib/2.16/flagme_1.16.2.zip mac.binary.ver: bin/macosx/contrib/2.16/flagme_1.16.2.tgz vignettes: vignettes/flagme/inst/doc/flagme.pdf vignetteTitles: Using flagme -- Fragment-level analysis of GCMS-based metabolomics data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flagme/inst/doc/flagme.R Package: flowClust Version: 3.0.0 Depends: R(>= 2.5.0),methods, Biobase, graph, RBGL,ellipse, flowViz, mnormt, corpcor, flowCore(>= 1.11.23), clue Imports: BiocGenerics, MCMCpack Suggests: parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 748be8eb9aedb6045e62c9c52dc53502 NeedsCompilation: yes Title: Clustering for Flow Cytometry Description: Robust model-based clustering using a t-mixture model with Box-Cox transformation. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. biocViews: Clustering, Bioinformatics, Visualization, FlowCytometry Author: Raphael Gottardo , Kenneth Lo , Greg Finak Maintainer: Raphael Gottardo source.ver: src/contrib/flowClust_3.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowClust_3.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowClust_3.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowClust_3.0.0.tgz vignettes: vignettes/flowClust/inst/doc/flowClust.pdf vignetteTitles: flowClust package hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowClust/inst/doc/flowClust.R dependsOnMe: flowMerge importsMe: flowPhyto, flowTrans, flowType suggestsMe: BiocGenerics Package: flowCore Version: 1.26.3 Depends: R (>= 2.10.0), Biobase, rrcov Imports: Biobase, BiocGenerics (>= 0.1.14), feature, graph, graphics, grDevices, MASS, methods, rrcov, stats, utils, stats4 Suggests: Rgraphviz, flowViz, ncdf License: Artistic-2.0 Archs: i386, x64 MD5sum: 0d57e6ac9e22233f67500fa2c6b4384d NeedsCompilation: yes Title: flowCore: Basic structures for flow cytometry data Description: Provides S4 data structures and basic functions to deal with flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: B. Ellis, P. Haaland, F. Hahne, N. Le Meur, N. Gopalakrishnan Maintainer: M.Jiang source.ver: src/contrib/flowCore_1.26.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowCore_1.26.3.zip win64.binary.ver: bin/windows64/contrib/2.16/flowCore_1.26.3.zip mac.binary.ver: bin/macosx/contrib/2.16/flowCore_1.26.3.tgz vignettes: vignettes/flowCore/inst/doc/HowTo-flowCore.pdf vignetteTitles: Basic Functions for Flow Cytometry Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowCore/inst/doc/HowTo-flowCore.R htmlDocs: vignettes/flowCore/inst/doc/fcs3.html htmlTitles: "Data File Standard for Flow Cytometry, Version FCS3.0" dependsOnMe: flowFP, flowMerge, flowStats, flowTrans, flowUtils, flowViz, flowWorkspace, iFlow, ncdfFlow, plateCore importsMe: flowFlowJo, flowFP, flowMeans, flowPhyto, flowQ, flowStats, flowTrans, flowType, flowUtils, flowViz, iFlow, plateCore, spade suggestsMe: flowQB, RchyOptimyx Package: flowFlowJo Version: 1.18.0 Depends: R (>= 2.5.0), MASS, Imports: flowCore, XML (>= 1.96), methods, Biobase License: GPL (>=3) MD5sum: 3537bb3028689e9fe8b2a3565f6f439a NeedsCompilation: no Title: Tools for extracting information from a FlowJo workspace and working with the data in the flowCore paradigm. Description: FlowJo is a commercial GUI based software package from TreeStar Inc. for the visualization and analysis of flow cytometry data. One of the FlowJo standard export file types is the "FlowJo Workspace". This is an XML document that describes files and manipulations that have been performed in the FlowJo GUI environment. This package can take apart the FlowJo workspace and deliver the data into R in the flowCore paradigm. biocViews: FlowCytometry Author: John J. Gosink Maintainer: John J. Gosink source.ver: src/contrib/flowFlowJo_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowFlowJo_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowFlowJo_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowFlowJo_1.18.0.tgz vignettes: vignettes/flowFlowJo/inst/doc/flowFlowJo.pdf vignetteTitles: Basic Functions for working with FlowJo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowFlowJo/inst/doc/flowFlowJo.R Package: flowFP Version: 1.18.0 Depends: R (>= 2.10), flowCore, flowViz Imports: Biobase, BiocGenerics (>= 0.1.6), flowCore, flowViz, graphics, grDevices, methods, stats, stats4 Suggests: RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: ca71ac3729eb856712534f7b6ffb7bd7 NeedsCompilation: yes Title: Fingerprinting for Flow Cytometry Description: Fingerprint generation of flow cytometry data, used to facilitate the application of machine learning and datamining tools for flow cytometry. biocViews: Bioinformatics, FlowCytometry, CellBasedAssays, Clustering, Visualization Author: Herb Holyst , Wade Rogers Maintainer: Herb Holyst source.ver: src/contrib/flowFP_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowFP_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowFP_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowFP_1.18.0.tgz vignettes: vignettes/flowFP/inst/doc/flowFP_HowTo.pdf vignetteTitles: Fingerprinting for Flow Cytometry hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowFP/inst/doc/flowFP_HowTo.R Package: flowMeans Version: 1.12.0 Depends: R (>= 2.10.0) Imports: Biobase, graphics, grDevices, methods, rrcov, stats, feature, flowCore License: Artistic-2.0 MD5sum: 06d3a2c43e626a4867fe6034a9790c96 NeedsCompilation: no Title: Non-parametric Flow Cytometry Data Gating Description: Identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection. Note: R 2.11.0 or newer is required. biocViews: Bioinformatics, FlowCytometry, CellBiology, Clustering, Cancer, FlowCytData, StemCells, HIV Author: Nima Aghaeepour Maintainer: Nima Aghaeepour source.ver: src/contrib/flowMeans_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowMeans_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowMeans_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowMeans_1.12.0.tgz vignettes: vignettes/flowMeans/inst/doc/flowMeans.pdf vignetteTitles: flowMeans: Non-parametric Flow Cytometry Data Gating hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMeans/inst/doc/flowMeans.R importsMe: flowPhyto, flowType Package: flowMerge Version: 2.8.0 Depends: Rgraphviz, flowClust, flowCore, methods,snow,foreach,graph,feature Imports: rrcov, flowClust,flowCore, graphics, methods, rrcov, stats, utils, BiocGenerics (>= 0.1.6) Suggests: Rgraphviz Enhances: doMC, multicore License: Artistic-2.0 MD5sum: 5c69bc7854e0bb7f8e1f6a6bb91a27b5 NeedsCompilation: no Title: Cluster Merging for Flow Cytometry Data Description: Merging of mixture components for model-based automated gating of flow cytometry data using the flowClust framework. Note: users should have a working copy of flowClust 2.0 installed. biocViews: Bioinformatics, Clustering, FlowCytometry Author: Greg Finak , Raphael Gottardo Maintainer: Greg Finak source.ver: src/contrib/flowMerge_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowMerge_2.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowMerge_2.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowMerge_2.8.0.tgz vignettes: vignettes/flowMerge/inst/doc/flowMerge.pdf vignetteTitles: flowMerge package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMerge/inst/doc/flowMerge.R importsMe: flowType Package: flowPeaks Version: 1.2.0 Depends: R (>= 2.12.0) Enhances: flowCore License: Artistic-1.0 Archs: i386, x64 MD5sum: b37c23a7965b9b39e5796545d6810f23 NeedsCompilation: yes Title: An R package for flow data clustering Description: A fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means. biocViews: Flow cytometry, Clustering, Gating, Bioinformatics Author: Yongchao Ge Maintainer: Yongchao Ge source.ver: src/contrib/flowPeaks_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowPeaks_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowPeaks_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowPeaks_1.2.0.tgz vignettes: vignettes/flowPeaks/inst/doc/flowPeaks-guide.pdf vignetteTitles: Tutorial of flowPeaks package hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowPeaks/inst/doc/flowPeaks-guide.R Package: flowPhyto Version: 1.12.1 Depends: R (>= 1.8.0) Imports: flowClust, flowCore, flowMeans, TTR Suggests: RPostgreSQL, zoo, maps, mapdata, plotrix License: Artistic-2.0 MD5sum: 98f6e8e875304060edd9e3c4e8100f0f NeedsCompilation: no Title: Methods for Continuous Flow Cytometry Description: Automated Analysis of Continuous Flow Cytometry Data. biocViews: FlowCytometry, DataImport, QualityControl, Classification, Bioinformatics, Visualization, Clustering Author: Francois Ribalet and David M. Schruth Maintainer: Chris Berthiaume URL: http://seaflow.ocean.washington.edu source.ver: src/contrib/flowPhyto_1.12.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowPhyto_1.12.1.zip win64.binary.ver: bin/windows64/contrib/2.16/flowPhyto_1.12.1.zip mac.binary.ver: bin/macosx/contrib/2.16/flowPhyto_1.12.1.tgz vignettes: vignettes/flowPhyto/inst/doc/flowPhyto.pdf vignetteTitles: flowPhyto hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowPhyto/inst/doc/flowPhyto.R Package: flowPlots Version: 1.8.0 Depends: R (>= 2.13.0), methods Suggests: vcd License: Artistic-2.0 MD5sum: 9494f0cd2b8921d4058b1ccaa871a375 NeedsCompilation: no Title: flowPlots: analysis plots and data class for gated flow cytometry data Description: Graphical displays with embedded statistical tests for gated ICS flow cytometry data, and a data class which stores "stacked" data and has methods for computing summary measures on stacked data, such as marginal and polyfunctional degree data. biocViews: FlowCytometry, CellBasedAssays, Visualization, DataRepresentation Author: N. Hawkins, S. Self Maintainer: N. Hawkins source.ver: src/contrib/flowPlots_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowPlots_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowPlots_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowPlots_1.8.0.tgz vignettes: vignettes/flowPlots/inst/doc/flowPlots.pdf vignetteTitles: Plots with Embedded Tests for Gated Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowPlots/inst/doc/flowPlots.R Package: flowQ Version: 1.20.0 Depends: R (>= 2.10.0), methods, BiocGenerics (>= 0.1.3), outliers, lattice, flowViz, mvoutlier, bioDist, parody, RColorBrewer, latticeExtra Imports: methods, BiocGenerics, geneplotter, flowCore, flowViz, IRanges Suggests: flowStats License: Artistic-2.0 MD5sum: 37f87052cfb75a643267b0f708687834 NeedsCompilation: no Title: Quality control for flow cytometry Description: Provides quality control and quality assessment tools for flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: R. Gentleman, F. Hahne, J. Kettman, N. Le Meur, N. Gopalakrishnan Maintainer: Mike Jiang SystemRequirements: ImageMagick source.ver: src/contrib/flowQ_1.20.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/flowQ_1.20.0.tgz vignettes: vignettes/flowQ/inst/doc/DataQualityAssessment.pdf, vignettes/flowQ/inst/doc/Extending-flowQ.pdf, vignettes/flowQ/inst/doc/flowQStructure.pdf, vignettes/flowQ/inst/doc/stainInfo.pdf vignetteTitles: Data Quality Assesment for Ungated Flow Cytometry Data, Basic Functions for Flow Cytometry Data, flowQStructure.pdf, stainInfo.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowQ/inst/doc/DataQualityAssessment.R, vignettes/flowQ/inst/doc/Extending-flowQ.R Package: flowQB Version: 1.2.0 Imports: Biobase, graphics,methods, flowCore,stats Suggests: flowCore License: Artistic-2.0 MD5sum: 0aa6ef22e2fe36c2958c87bc5e3ad6a2 NeedsCompilation: no Title: Flow cytometer sensitivity-Automatic Q and B Calculations. Description: flowQB is a fully automated R Bioconductor package to calculate automatically the detector efficiency (Q), optical background (B), and electronic noise. biocViews: FlowCytometry Author: Faysal El Khettabi Maintainer: Faysal El Khettabi source.ver: src/contrib/flowQB_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowQB_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowQB_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowQB_1.2.0.tgz vignettes: vignettes/flowQB/inst/doc/flowQB_Sweave_.pdf vignetteTitles: flowQB package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowQB/inst/doc/flowQB_Sweave_.R Package: flowStats Version: 1.18.0 Depends: R (>= 2.10), flowCore (>= 1.10.0), fda (>= 2.2.6), mvoutlier, cluster, flowWorkspace (>= 1.5.68) Imports: BiocGenerics, MASS, flowViz, flowCore, fda (>= 2.2.6), Biobase, methods, grDevices, graphics, stats, utils, KernSmooth, lattice,compositions Suggests: flowViz, xtable Enhances: RBGL,ncdfFlow,graph License: Artistic-2.0 MD5sum: 4e16a5e08ecfd3f93d9e2cd58a23c571 NeedsCompilation: no Title: Statistical methods for the analysis of flow cytometry data Description: Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package. biocViews: FlowCytometry, CellBasedAssays, Bioinformatics Author: Florian Hahne, Nishant Gopalakrishnan, Alireza Hadj Khodabakhshi, Chao-Jen Wong, Kyongryun Lee Maintainer: Greg Finak and Mike Jiang source.ver: src/contrib/flowStats_1.18.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/flowStats_1.18.0.tgz vignettes: vignettes/flowStats/inst/doc/GettingStartedWithFlowStats.pdf vignetteTitles: flowStats Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowStats/inst/doc/GettingStartedWithFlowStats.R dependsOnMe: iFlow importsMe: iFlow suggestsMe: flowQ Package: flowTrans Version: 1.12.0 Depends: R (>= 2.11.0), flowCore, flowViz,flowClust Imports: flowCore, methods, flowViz, stats, flowClust License: Artistic-2.0 MD5sum: 63d3155bf6cd43f90b4a872bac03356b NeedsCompilation: no Title: Parameter Optimization for Flow Cytometry Data Transformation Description: Profile maximum likelihood estimation of parameters for flow cytometry data transformations. biocViews: Bioinformatics, FlowCytometry Author: Greg Finak , Juan Manuel-Perez , Raphael Gottardo Maintainer: Greg Finak source.ver: src/contrib/flowTrans_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowTrans_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowTrans_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowTrans_1.12.0.tgz vignettes: vignettes/flowTrans/inst/doc/flowTrans.pdf vignetteTitles: flowTrans package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowTrans/inst/doc/flowTrans.R Package: flowType Version: 1.6.0 Depends: R (>= 2.10) Imports: Biobase, graphics, grDevices, methods, flowCore, flowMeans, sfsmisc, rrcov, flowClust, flowMerge, stats Suggests: xtable License: Artistic-2.0 MD5sum: 5dc2d1f32856eedd2999bac7b5834af7 NeedsCompilation: no Title: Phenotyping Flow Cytometry Assays Description: Phenotyping Flow Cytometry Assays using multidimentional expantion of single dimentional partitions. biocViews: FlowCytometry Author: Nima Aghaeepour Maintainer: Nima Aghaeepour source.ver: src/contrib/flowType_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowType_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowType_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowType_1.6.0.tgz vignettes: vignettes/flowType/inst/doc/flowType.pdf vignetteTitles: flowType package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowType/inst/doc/flowType.R suggestsMe: RchyOptimyx Package: flowUtils Version: 1.20.0 Depends: R (>= 2.2.0), flowCore (>= 1.2.0) Imports: Biobase, flowCore, graph, methods, RUnit, stats, utils, XML, flowViz Suggests: gatingMLData License: Artistic-2.0 MD5sum: d5873c37bad91039804d1f95846c9e57 NeedsCompilation: no Title: Utilities for flow cytometry Description: Provides utilities for flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: Gopalakrishnan N, F. Hahne, B. Ellis, R. Gentleman M. Dalphin,N. Le Meur, B. Purcell. Maintainer: Nishant Gopalakrishnan source.ver: src/contrib/flowUtils_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowUtils_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowUtils_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowUtils_1.20.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: flowViz Version: 1.24.0 Depends: R (>= 2.7.0), flowCore (>= 1.5.17), lattice, grDevices Imports: stats4, Biobase, flowCore, graphics, grDevices, grid, KernSmooth, lattice, latticeExtra, MASS, methods, RColorBrewer, stats, utils, hexbin,IDPmisc Suggests: colorspace,RColorBrewer License: Artistic-2.0 MD5sum: 225a3d543ea0e82a309b48a4eed02ab3 NeedsCompilation: no Title: Visualization for flow cytometry Description: Provides visualization tools for flow cytometry data. biocViews: Infrastructure, Flowcytometry, CellBasedAssays, Visualization Author: B. Ellis, R. Gentleman, F. Hahne, N. Le Meur, D. Sarkar Maintainer: Mike Jiang source.ver: src/contrib/flowViz_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/flowViz_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/flowViz_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/flowViz_1.24.0.tgz vignettes: vignettes/flowViz/inst/doc/filters.pdf vignetteTitles: Visualizing Gates with Flow Cytometry Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowViz/inst/doc/filters.R dependsOnMe: flowClust, flowFP, flowQ, flowWorkspace, iFlow, plateCore importsMe: flowFP, flowQ, flowStats, flowTrans, flowUtils, iFlow suggestsMe: flowCore, flowStats, spade Package: flowWorkspace Version: 1.6.1 Depends: R (>= 2.16.0),Rcpp (>= 0.9.9),Cairo, BiocGenerics, methods, RBGL, graph, XML, flowCore (>= 1.25.9), flowViz (>= 1.23.1), Biobase, IDPmisc, tools,hexbin,gridExtra,Rgraphviz,ncdfFlow(>= 1.5.19) Imports: Biobase, XML,flowCore, graph, graphics, lattice, methods, stats, stats4, utils LinkingTo: Rcpp,ncdfFlow Suggests: testthat, flowWorkspaceData Enhances: multicore,Rmpi License: Artistic-2.0 MD5sum: c083e495447db906e124a725adabd92c NeedsCompilation: yes Title: Import flowJo Workspaces into BioConductor and replicate flowJo gating with flowCore Description: This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis. biocViews: FlowCytometry, DataImport, Preprocessing, DataRepresentation Author: Greg Finak, Mike Jiang, Mose Andre Maintainer: Greg Finak ,Mike Jiang source.ver: src/contrib/flowWorkspace_1.6.1.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/flowWorkspace_1.6.1.tgz vignettes: vignettes/flowWorkspace/inst/doc/flowWorkspace.pdf vignetteTitles: Importing flowJo Workspaces into R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowWorkspace/inst/doc/flowWorkspace.R dependsOnMe: flowStats Package: fmcsR Version: 1.2.1 Depends: R (>= 2.10.0), ChemmineR, methods License: Artistic-2.0 Archs: i386, x64 MD5sum: f7071958dd1f6ad94e147acedee2118e NeedsCompilation: yes Title: Flexible Maximum Common Substructure (FMCS) Searching Description: The fmcsR package introduces an efficient maximum common substructure (MCS) algorithms combined with a novel matching strategy that allows for atom and/or bond mismatches in the substructures shared among two small molecules. The resulting flexible MCSs (FMCSs) are often larger than strict MCSs, resulting in the identification of more common features in their source structures, as well as a higher sensitivity in finding compounds with weak structural similarities. The fmcsR package provides several utilities to use the FMCS algorithm for pairwise compound comparisons, structure similarity searching and clustering. biocViews: MicrotitrePlateAssay, CellBasedAssays, Visualization, Infrastructure, DataImport, Clustering, Bioinformatics, Proteomics Author: Yan Wang, Tyler Backman, Kevin Horan, Thomas Girke Maintainer: ChemmineR Team URL: http://manuals.bioinformatics.ucr.edu/home/chemminer source.ver: src/contrib/fmcsR_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/fmcsR_1.2.1.zip win64.binary.ver: bin/windows64/contrib/2.16/fmcsR_1.2.1.zip mac.binary.ver: bin/macosx/contrib/2.16/fmcsR_1.2.1.tgz vignettes: vignettes/fmcsR/inst/doc/fmcsR.pdf vignetteTitles: gpls Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fmcsR/inst/doc/fmcsR.R suggestsMe: ChemmineR Package: frma Version: 1.12.0 Depends: R (>= 2.10.0), Biobase (>= 2.6.0) Imports: Biobase, MASS, DBI, affy, methods, oligo, oligoClasses, preprocessCore, utils, BiocGenerics Suggests: hgu133afrmavecs, frmaExampleData License: GPL (>= 2) MD5sum: 1b15fe2f0ec89fd35b91f089c17812af NeedsCompilation: no Title: Frozen RMA and Barcode Description: Preprocessing and analysis for single microarrays and microarray batches. biocViews: Software, Microarray, Preprocessing Author: Matthew N. McCall , Rafael A. Irizarry , with contributions from Terry Therneau Maintainer: Matthew N. McCall URL: http://bioconductor.org source.ver: src/contrib/frma_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/frma_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/frma_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/frma_1.12.0.tgz vignettes: vignettes/frma/inst/doc/frma.pdf vignetteTitles: frma: Preprocessing for single arrays and array batches hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/frma/inst/doc/frma.R importsMe: ChIPXpress suggestsMe: frmaTools Package: frmaTools Version: 1.12.0 Depends: R (>= 2.10.0), affy Imports: Biobase, DBI, methods, preprocessCore, stats, utils Suggests: oligo, pd.huex.1.0.st.v2, pd.hugene.1.0.st.v1, frma, affyPLM, hgu133aprobe, hgu133atagprobe, hgu133plus2probe, hgu133acdf, hgu133atagcdf, hgu133plus2cdf, hgu133afrmavecs, frmaExampleData License: GPL (>= 2) MD5sum: b5d8833b2670f958fd112001037c5764 NeedsCompilation: no Title: Frozen RMA Tools Description: Tools for advanced use of the frma package. biocViews: Software, Microarray, Preprocessing Author: Matthew N. McCall , Rafael A. Irizarry Maintainer: Matthew N. McCall URL: http://bioconductor.org source.ver: src/contrib/frmaTools_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/frmaTools_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/frmaTools_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/frmaTools_1.12.0.tgz vignettes: vignettes/frmaTools/inst/doc/frmaTools.pdf vignetteTitles: frmaTools: Create packages containing the vectors used by frma. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/frmaTools/inst/doc/frmaTools.R Package: FunciSNP Version: 1.2.0 Depends: R (>= 2.14.0), ggplot2, TxDb.Hsapiens.UCSC.hg19.knownGene, FunciSNP.data Imports: AnnotationDbi, IRanges, Rsamtools (>= 1.6.1), rtracklayer(>= 1.14.1), methods, ChIPpeakAnno (>= 2.2.0), GenomicRanges, VariantAnnotation, plyr, org.Hs.eg.db, snpStats, ggplot2 (>= 0.9.0), reshape (>= 0.8.4), scales Enhances: parallel License: GPL-3 MD5sum: a528f334d276194451e37ab215683355 NeedsCompilation: no Title: Integrating Functional Non-coding Datasets with Genetic Association Studies to Identify Candidate Regulatory SNPs Description: FunciSNP integrates information from GWAS, 1000genomes and chromatin feature to identify functional SNP in coding or non-coding regions. biocViews: Infrastructure, DataRepresentation, DataImport, SequenceMatching, Annotation Author: Simon G. Coetzee and Houtan Noushmehr, PhD Maintainer: Simon G. Coetzee URL: http://coetzeeseq.usc.edu/publication/Coetzee_SG_et_al_2012/ source.ver: src/contrib/FunciSNP_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/FunciSNP_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/FunciSNP_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/FunciSNP_1.2.0.tgz vignettes: vignettes/FunciSNP/inst/doc/FunciSNP_vignette.pdf, vignettes/FunciSNP/inst/doc/UCSC_genomeviewer_glioma.pdf vignetteTitles: FunciSNP Vignette, UCSC_genomeviewer_glioma.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/FunciSNP/inst/doc/FunciSNP_vignette.R Package: gaga Version: 2.6.0 Depends: R (>= 2.8.0), Biobase, coda, EBarrays, mgcv Enhances: multicore License: GPL (>= 2) Archs: i386, x64 MD5sum: 2b97d12d19da58784e42f56bac976f8d NeedsCompilation: yes Title: GaGa hierarchical model for high-throughput data analysis Description: Implements the GaGa model for high-throughput data analysis, including differential expression analysis, supervised gene clustering and classification. Additionally, it performs sequential sample size calculations using the GaGa and LNNGV models (the latter from EBarrays package). biocViews: OneChannel,MassSpectrometry,MultipleComparisons,DifferentialExpression,Classification Author: David Rossell . Maintainer: David Rossell source.ver: src/contrib/gaga_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gaga_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gaga_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gaga_2.6.0.tgz vignettes: vignettes/gaga/inst/doc/gagamanual.pdf vignetteTitles: Manual for the gaga library hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaga/inst/doc/gagamanual.R dependsOnMe: casper Package: gage Version: 2.10.0 Depends: R (>= 2.10) Imports: graph Suggests: pathview, gageData, GO.db, KEGG.db, org.Hs.eg.db, hgu133a.db, GSEABase License: GPL (>=2.0) MD5sum: 911fa0f4549ab068940c9ab39a4f9ee8 NeedsCompilation: no Title: Generally Applicable Gene-set Enrichment for Pathway Analysis Description: GAGE is a published method for gene set or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods. biocViews: Pathways, GO, DifferentialExpression, Microarray, OneChannel, TwoChannel, RNAseq, Genetics, MultipleComparisons, GeneSetEnrichment Author: Weijun Luo Maintainer: Weijun Luo URL: http://www.biomedcentral.com/1471-2105/10/161 source.ver: src/contrib/gage_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gage_2.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gage_2.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gage_2.10.0.tgz vignettes: vignettes/gage/inst/doc/dataPrep.pdf, vignettes/gage/inst/doc/gage.pdf vignetteTitles: Gene set and data preparation, Generally Applicable Gene-set/Pathway Analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gage/inst/doc/dataPrep.R, vignettes/gage/inst/doc/gage.R suggestsMe: pathview Package: gaggle Version: 1.28.0 Depends: R (>= 2.3.0), rJava (>= 0.4), graph (>= 1.10.2), RUnit (>= 0.4.17) License: GPL version 2 or newer MD5sum: 513895c1b084e9ab0b145c33ac51bddd NeedsCompilation: no Title: Broadcast data between R and Gaggle Description: This package contains functions enabling data exchange between R and Gaggle enabled bioinformatics software, including Cytoscape, Firegoose and Gaggle Genome Browser. biocViews: ConnectTools, NetworkVisualization, Annotation, GraphsAndNetworks, DataImport Author: Paul Shannon Maintainer: Christopher Bare URL: http://gaggle.systemsbiology.net/docs/geese/r/ source.ver: src/contrib/gaggle_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gaggle_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gaggle_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gaggle_1.28.0.tgz vignettes: vignettes/gaggle/inst/doc/gaggle.pdf vignetteTitles: Gaggle Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaggle/inst/doc/gaggle.R Package: gaia Version: 2.4.0 Depends: R (>= 2.10) License: GPL-2 MD5sum: 57cd8ad1ec3b6f45466eab2095e34c78 NeedsCompilation: no Title: GAIA: An R package for genomic analysis of significant chromosomal aberrations. Description: This package allows to assess the statistical significance of chromosomal aberrations. biocViews: aCGH, CopyNumberVariants Author: Sandro Morganella et al. Maintainer: S. Morganella source.ver: src/contrib/gaia_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gaia_2.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gaia_2.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gaia_2.4.0.tgz vignettes: vignettes/gaia/inst/doc/gaia.pdf vignetteTitles: gaia hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaia/inst/doc/gaia.R Package: gCMAP Version: 1.4.1 Depends: GSEABase, limma (>= 3.15.14) Imports: Biobase, BiocGenerics, methods, GSEAlm, Category, bigmemory, bigmemoryExtras (>= 1.1.2), Matrix (>= 1.0.9), parallel, annotate, genefilter, AnnotationDbi Suggests: DESeq, KEGG.db, reactome.db, RUnit, GO.db, mgsa License: Artistic-2.0 OS_type: unix MD5sum: 15c10d41abe337acfec4532966bc3b42 NeedsCompilation: no Title: Tools for Connectivity Map-like analyses Description: The gCMAP package provides a toolkit for comparing differential gene expression profiles through gene set enrichment analysis. Starting from normalized microarray or RNA-seq gene expression values (stored in lists of ExpressionSet and CountDataSet objects) the package performs differential expression analysis using the limma or DESeq packages. Supplying a simple list of gene identifiers, global differential expression profiles or data from complete experiments as input, users can use a unified set of several well-known gene set enrichment analysis methods to retrieve experiments with similar changes in gene expression. To take into account the directionality of gene expression changes, gCMAPQuery introduces the SignedGeneSet class, directly extending GeneSet from the GSEABase package. To increase performance of large queries, multiple gene sets are stored as sparse incidence matrices within CMAPCollection eSets. gCMAP offers implementations of 1. Fisher's exact test (Fisher, J R Stat Soc, 1922) 2. The "connectivity map" method (Lamb et al, Science, 2006) 3. Parametric and non-parametric t-statistic summaries (Jiang & Gentleman, Bioinformatics, 2007) and 4. Wilcoxon / Mann-Whitney rank sum statistics (Wilcoxon, Biometrics Bulletin, 1945) as well as wrappers for the 5. camera (Wu & Smyth, Nucleic Acid Res, 2012) 6. mroast and romer (Wu et al, Bioinformatics, 2010) functions from the limma package and 7. wraps the gsea method from the mgsa package (Bauer et al, NAR, 2010). All methods return CMAPResult objects, an S4 class inheriting from AnnotatedDataFrame, containing enrichment statistics as well as annotation data and providing simple high-level summary plots. biocViews: Bioinformatics, Microarray, Software, Pathways, Annotation Author: Thomas Sandmann , Richard Bourgon and Sarah Kummerfeld Maintainer: Thomas Sandmann source.ver: src/contrib/gCMAP_1.4.1.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/gCMAP_1.4.1.tgz vignettes: vignettes/gCMAP/inst/doc/diffExprAnalysis.pdf, vignettes/gCMAP/inst/doc/gCMAP.pdf vignetteTitles: main, gCMAP classes and methods hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gCMAP/inst/doc/diffExprAnalysis.R, vignettes/gCMAP/inst/doc/gCMAP.R, vignettes/gCMAP/inst/doc/keggReactome.R dependsOnMe: gCMAPWeb Package: gCMAPWeb Version: 1.0.3 Depends: brew, gCMAP (>= 1.3.0), R (>= 2.15.0), yaml Imports: Biobase, annotate, AnnotationDbi, bigmemory, bigmemoryExtras, BiocGenerics, brew, graphics, grDevices, GSEABase, hwriter, IRanges, methods, parallel, Rook, stats, utils Suggests: org.Hs.eg.db, org.Mm.eg.db, ArrayExpress, affy, hgfocus.db, ArrayExpress, hgu133a.db, mgug4104a.db, RUnit License: Artistic-2.0 MD5sum: 8ff5dc953a20d199d24958ce4c618292 NeedsCompilation: no Title: A web interface for gene-set enrichment analyses Description: The gCMAPWeb R package provides a graphical user interface for the gCMAP package. gCMAPWeb uses the Rook package and can be used either on a local machine, leveraging R's internal web server, or run on a dedicated rApache web server installation. gCMAPWeb allows users to search their own data sources and instructions to generate reference datasets from public repositories are included with the package. The package supports three common types of analyses, specifically queries with 1. one or two sets of query gene identifiers, whose members are expected to show changes in gene expression in a consistent direction. For example, an up-regulated gene set might contain genes activated by a transcription factor, a down-regulated geneset targets repressed by the same factor. 2. a single set of query gene identifiers, whose members are expected to show divergent differential expression (non-directional query). For example, members of a particular signaling pathway, some of which may be up- some down-regulated in response to a stimulus. 3. a query with the complete results of a differential expression profiling experiment. For example, gene identifiers and z-scores from a previous perturbation experiment. gCMAPWeb accepts three types of identifiers: EntreIds, gene Symbols and microarray probe ids and can be configured to work with any species supported by Bioconductor. For each query submission, significantly similar reference datasets will be identified and reported in graphical and tabular form. biocViews: Bioinformatics, GUI, GeneSetEnrichment, Visualization Author: Thomas Sandmann Maintainer: Thomas Sandmann source.ver: src/contrib/gCMAPWeb_1.0.3.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/gCMAPWeb_1.0.3.tgz vignettes: vignettes/gCMAPWeb/inst/doc/gCMAPWeb.pdf, vignettes/gCMAPWeb/inst/doc/referenceDatasets.pdf, vignettes/gCMAPWeb/inst/doc/tutorial.pdf vignetteTitles: gCMAPWeb configuration, Recreating the Broad Connectivity Map v1, tutorial.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gCMAPWeb/inst/doc/gCMAPWeb.R, vignettes/gCMAPWeb/inst/doc/referenceDatasets.R Package: gcrma Version: 2.32.0 Depends: R (>= 2.6.0), affy (>= 1.23.2), graphics, methods, stats, utils Imports: Biobase, affy (>= 1.23.2), affyio (>= 1.13.3), IRanges, Biostrings (>= 2.11.32), splines, BiocInstaller Suggests: affydata, tools, splines, hgu95av2cdf, hgu95av2probe License: LGPL Archs: i386, x64 MD5sum: 5295580f9b5ddc10ee1d40e17c383dcd NeedsCompilation: yes Title: Background Adjustment Using Sequence Information Description: Background adjustment using sequence information biocViews: Microarray, OneChannel, Preprocessing Author: Jean(ZHIJIN) Wu, Rafael Irizarry with contributions from James MacDonald Jeff Gentry Maintainer: Z. Wu source.ver: src/contrib/gcrma_2.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gcrma_2.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gcrma_2.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gcrma_2.32.0.tgz vignettes: vignettes/gcrma/inst/doc/gcrma2.0.pdf vignetteTitles: gcrma1.2 hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gcrma/inst/doc/gcrma2.0.R dependsOnMe: affyILM, affylmGUI, affyPLM, bgx, maskBAD, simpleaffy, webbioc importsMe: affycoretools, simpleaffy, virtualArray suggestsMe: AffyExpress, ArrayTools, BiocCaseStudies, panp Package: genArise Version: 1.36.0 Depends: R (>= 1.7.1), locfit, tkrplot, methods Imports: graphics, grDevices, methods, stats, tcltk, utils, xtable License: file LICENSE License_restricts_use: yes MD5sum: d7c8300cd31eeaf2269a6c479a4968ca NeedsCompilation: no Title: Microarray Analysis tool Description: genArise is an easy to use tool for dual color microarray data. Its GUI-Tk based environment let any non-experienced user performs a basic, but not simple, data analysis just following a wizard. In addition it provides some tools for the developer. biocViews: Microarray, TwoChannel, Preprocessing Author: Ana Patricia Gomez Mayen ,\\ Gustavo Corral Guille , \\ Lina Riego Ruiz ,\\ Gerardo Coello Coutino Maintainer: IFC Development Team URL: http://www.ifc.unam.mx/genarise source.ver: src/contrib/genArise_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genArise_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genArise_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genArise_1.36.0.tgz vignettes: vignettes/genArise/inst/doc/genArise.pdf vignetteTitles: genAriseGUI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/genArise/inst/doc/genArise.R Package: GeneAnswers Version: 2.2.1 Depends: R (>= 2.10.0), igraph, RCurl, annotate, Biobase (>= 1.12.0), methods, XML, RSQLite, MASS, Heatplus, RColorBrewer Imports: RBGL, annotate Suggests: GO.db, KEGG.db, reactome.db, biomaRt, AnnotationDbi, org.Hs.eg.db, org.Rn.eg.db, org.Mm.eg.db, org.Dm.eg.db, graph License: LGPL (>= 2) MD5sum: b760038b10171c3af03bcc8eb377163a NeedsCompilation: no Title: Integrated Interpretation of Genes Description: GeneAnswers provides an integrated tool for biological or medical interpretation of the given one or more groups of genes by means of statistical test. biocViews: Infrastructure, DataRepresentation, Visualization, GraphsAndNetworks Author: Gang Feng, Pan Du, Tian Xia, Warren Kibbe and Simon Lin Maintainer: Gang Feng , Pan Du and Tian Xia source.ver: src/contrib/GeneAnswers_2.2.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneAnswers_2.2.1.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneAnswers_2.2.1.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneAnswers_2.2.1.tgz vignettes: vignettes/GeneAnswers/inst/doc/geneAnswers.pdf vignetteTitles: GeneAnswers hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneAnswers/inst/doc/GeneAnswersCWAnnotation.R, vignettes/GeneAnswers/inst/doc/geneAnswers.R, vignettes/GeneAnswers/inst/doc/geneFunctionSummarize.R Package: GENE.E Version: 1.1.0 Depends: R (>= 2.7.0), h5r (>= 1.4.1), RCurl (>= 1.6-6) Imports: h5r, RCurl Suggests: RUnit, BiocGenerics, knitr, golubEsets (>= 1.0) License: GPL-2 MD5sum: f87b72ac1859fc62e5a14bf43c654472 NeedsCompilation: no Title: Interact with GENE-E from R Description: Interactive exploration of matrices in GENE-E. biocViews: ConnectTools Author: Joshua Gould Maintainer: Joshua Gould URL: http://www.broadinstitute.org/cancer/software/GENE-E SystemRequirements: GENE-E software. VignetteBuilder: knitr source.ver: src/contrib/GENE.E_1.1.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GENE.E_1.1.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GENE.E_1.1.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GENE.E_1.1.0.tgz vignettes: vignettes/GENE.E/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GENE.E/inst/doc/GENE.E-vignette.R htmlDocs: vignettes/GENE.E/inst/doc/GENE.E-vignette.html htmlTitles: "GENE.E Overview" Package: GeneExpressionSignature Version: 1.6.0 Depends: R (>= 2.13), Biobase, PGSEA Suggests: apcluster,GEOquery License: GPL-2 MD5sum: 04048b637e942fa4f0a47684b7f4437a NeedsCompilation: no Title: Gene Expression Signature based Similarity Metric Description: This package gives the implementations of the gene expression signature and its distance to each. Gene expression signature is represented as a list of genes whose expression is correlated with a biological state of interest. And its distance is defined using a nonparametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov statistic. Gene expression signature and its distance can be used to detect similarities among the signatures of drugs, diseases, and biological states of interest. biocViews: Bioinformatics, GeneExpression Author: Yang Cao Maintainer: Yang Cao , Fei Li ,Lu Han source.ver: src/contrib/GeneExpressionSignature_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneExpressionSignature_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneExpressionSignature_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneExpressionSignature_1.6.0.tgz vignettes: vignettes/GeneExpressionSignature/inst/doc/GeneExpressionSignature.pdf vignetteTitles: GeneExpressionSignature hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: genefilter Version: 1.42.0 Imports: AnnotationDbi, annotate (>= 1.13.7), Biobase (>= 1.99.10), graphics, methods, stats, survival Suggests: Biobase (>= 1.99.10), class, hgu95av2.db, methods, tkWidgets, ALL, ROC, DESeq, pasilla License: Artistic-2.0 Archs: i386, x64 MD5sum: 756a504a85fa970a9a2c8cffac2591c8 NeedsCompilation: yes Title: genefilter: methods for filtering genes from microarray experiments Description: Some basic functions for filtering genes biocViews: Bioinformatics, Microarray Author: R. Gentleman, V. Carey, W. Huber, F. Hahne Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/genefilter_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genefilter_1.42.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genefilter_1.42.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genefilter_1.42.0.tgz vignettes: vignettes/genefilter/inst/doc/howtogenefilter.pdf, vignettes/genefilter/inst/doc/howtogenefinder.pdf, vignettes/genefilter/inst/doc/independent_filtering.pdf, vignettes/genefilter/inst/doc/independent_filtering_plots.pdf vignetteTitles: Using the genefilter function to filter genes from a microarray dataset, How to find genes whose expression profile is similar to that of specified genes, Diagnostics for independent filtering, Additional plots for: Independent filtering increases power for detecting differentially expressed genes,, Bourgon et al.,, PNAS (2010) hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genefilter/inst/doc/howtogenefilter.R, vignettes/genefilter/inst/doc/howtogenefinder.R, vignettes/genefilter/inst/doc/independent_filtering_plots.R, vignettes/genefilter/inst/doc/independent_filtering.R dependsOnMe: a4Base, Agi4x44PreProcess, cellHTS, cellHTS2, charm, CNTools, GeneMeta, MLInterfaces, simpleaffy importsMe: affycoretools, affyQCReport, annmap, arrayQualityMetrics, Category, DESeq, DESeq2, eisa, gCMAP, GGBase, GSRI, methyAnalysis, methylumi, phenoTest, Ringo, simpleaffy, tilingArray, XDE suggestsMe: AffyExpress, annotate, ArrayTools, BiocCaseStudies, BioNet, Category, categoryCompare, clusterStab, codelink, factDesign, ffpe, GOstats, GSEAlm, GSVA, logicFS, lumi, MCRestimate, oligo, oneChannelGUI, phyloseq, pvac, qpgraph, rtracklayer, siggenes, SSPA, topGO, VanillaICE, XDE Package: genefu Version: 1.10.0 Depends: R (>= 2.10), survcomp, mclust, biomaRt Imports: amap Suggests: GeneMeta, breastCancerVDX, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerUNT, breastCancerNKI, rmeta, Biobase, xtable License: Artistic-2.0 MD5sum: 6485e5bd9d69b3adc6fa97d4dbfaf453 NeedsCompilation: no Title: Relevant Functions for Gene Expression Analysis, Especially in Breast Cancer. Description: Description: This package contains functions implementing various tasks usually required by gene expression analysis, especially in breast cancer studies: gene mapping between different microarray platforms, identification of molecular subtypes, implementation of published gene signatures, gene selection, survival analysis, ... biocViews: DifferentialExpression, GeneExpression, Visualization, Clustering, Classification Author: Benjamin Haibe-Kains, Markus Schroeder, Gianluca Bontempi, Christos Sotiriou, John Quackenbush Maintainer: Benjamin Haibe-Kains , Markus Schroeder URL: http://compbio.dfci.harvard.edu source.ver: src/contrib/genefu_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genefu_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genefu_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genefu_1.10.0.tgz vignettes: vignettes/genefu/inst/doc/genefu.pdf vignetteTitles: genefu An Introduction (HowTo) hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genefu/inst/doc/genefu.R Package: GeneGA Version: 1.10.0 Depends: seqinr, hash, methods License: GPL version 2 MD5sum: 445625a5c9d41af6488ee0701a1d6179 NeedsCompilation: no Title: Design gene based on both mRNA secondary structure and codon usage bias using Genetic algorithm Description: R based Genetic algorithm for gene expression optimization by considering both mRNA secondary structure and codon usage bias, GeneGA includes the information of highly expressed genes of almost 200 genomes. Meanwhile, Vienna RNA Package is needed to ensure GeneGA to function properly. biocViews: GeneExpression Author: Zhenpeng Li and Haixiu Huang Maintainer: Zhenpeng Li URL: http://www.tbi.univie.ac.at/~ivo/RNA/ source.ver: src/contrib/GeneGA_1.10.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/GeneGA_1.10.0.tgz vignettes: vignettes/GeneGA/inst/doc/GeneGA.pdf vignetteTitles: GeneGA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneGA/inst/doc/GeneGA.R Package: GeneGroupAnalysis Version: 1.6.0 Depends: R (>= 2.10), MCMCpack, GO.db, breastCancerVDX, rheumaticConditionWOLLBOLD, hgu133a.db, hgu133plus2.db Imports: AnnotationDbi, annotate, tcltk License: Artistic-2.0 Archs: i386, x64 MD5sum: 576b7450c172e5d436bdba89463c80e7 NeedsCompilation: yes Title: Gene Functional Class Analysis Description: R package providing functions to peform gene-set significance analysis over simple cross-sectional or time series data designs. biocViews: GeneExpression, DifferentialExpression, MultipleComparisons, CrossSectional, TimeCourse Author: Alejandro Quiroz-Zarate and John Quackenbush Maintainer: Alejandro Quiroz-Zarate URL: http://compbio.dfci.harvard.edu/ source.ver: src/contrib/GeneGroupAnalysis_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneGroupAnalysis_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneGroupAnalysis_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneGroupAnalysis_1.6.0.tgz vignettes: vignettes/GeneGroupAnalysis/inst/doc/GeneGroupAnalysis.pdf vignetteTitles: GeneGroupAnalysis: a package for performance assessment and comparison for survival analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneGroupAnalysis/inst/doc/GeneGroupAnalysis.R Package: GeneMeta Version: 1.32.0 Depends: R (>= 2.10), methods, Biobase (>= 2.5.5), genefilter Imports: methods, Biobase (>= 2.5.5) Suggests: RColorBrewer License: Artistic-2.0 MD5sum: 767f172af44a74016fddff099fcb8176 NeedsCompilation: no Title: MetaAnalysis for High Throughput Experiments Description: A collection of meta-analysis tools for analysing high throughput experimental data biocViews: Bioinformatics Author: Lara Lusa , R. Gentleman, M. Ruschhaupt Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GeneMeta_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneMeta_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneMeta_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneMeta_1.32.0.tgz vignettes: vignettes/GeneMeta/inst/doc/GeneMeta.pdf vignetteTitles: GeneMeta Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneMeta/inst/doc/GeneMeta.R suggestsMe: genefu, XDE Package: GeneNetworkBuilder Version: 1.2.0 Depends: R (>= 2.15.1), Rcpp (>= 0.9.13), graph Imports: plyr, graph LinkingTo: Rcpp Suggests: RUnit, BiocGenerics, Rgraphviz, XML, RCytoscape License: GPL (>= 2) Archs: i386, x64 MD5sum: d9f51f2bcd2a544683ec3655a254b280 NeedsCompilation: yes Title: Build Regulatory Network from ChIP-chip/ChIP-seq and Expression Data Description: Appliation for discovering direct or indirect targets of transcription factors using ChIP-chip or ChIP-seq, and microarray or RNA-seq gene expression data. Inputting a list of genes of potential targets of one TF from ChIP-chip or ChIP-seq, and the gene expression results, GeneNetworkBuilder generates a regulatory network of the TF. biocViews: HighThroughputSequencing, Microarray, GraphsAndNetworks Author: Jianhong Ou and Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/GeneNetworkBuilder_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneNetworkBuilder_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneNetworkBuilder_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneNetworkBuilder_1.2.0.tgz vignettes: vignettes/GeneNetworkBuilder/inst/doc/GeneNetworkBuilder.pdf vignetteTitles: GeneNetworkBuilder Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneNetworkBuilder/inst/doc/GeneNetworkBuilder.R Package: geneplotter Version: 1.38.0 Depends: R (>= 2.10),Biobase (>= 2.5.5), annotate, lattice Imports: annotate, AnnotationDbi, Biobase (>= 2.5.5), graphics, grDevices, grid, methods, RColorBrewer, stats, utils Suggests: Biobase (>= 2.5.5), Rgraphviz, annotate, fibroEset, hgu95av2.db, hu6800.db, hgu133a.db License: Artistic-2.0 MD5sum: 35239f58a04b2e6165b8dadb9bae4205 NeedsCompilation: no Title: Graphics related functions for Bioconductor Description: Some basic functions for plotting genetic data biocViews: Visualization Author: R. Gentleman, Biocore Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/geneplotter_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/geneplotter_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/geneplotter_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/geneplotter_1.38.0.tgz vignettes: vignettes/geneplotter/inst/doc/byChroms.pdf, vignettes/geneplotter/inst/doc/visualize.pdf vignetteTitles: How to assemble a chromLocation object, Visualization of Microarray Data hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geneplotter/inst/doc/byChroms.R, vignettes/geneplotter/inst/doc/visualize.R dependsOnMe: HMMcopy importsMe: biocGraph, DESeq, flowQ, IsoGeneGUI, MethylSeekR, RNAinteract, RNAither suggestsMe: BiocCaseStudies, biocGraph, Category, GOstats, maDB Package: geneRecommender Version: 1.32.0 Depends: R (>= 1.8.0), Biobase (>= 1.4.22), methods Imports: Biobase, methods, stats License: GPL (>= 2) MD5sum: a7dd9ff46b86b3e1cce592dafdae04cb NeedsCompilation: no Title: A gene recommender algorithm to identify genes coexpressed with a query set of genes Description: This package contains a targeted clustering algorithm for the analysis of microarray data. The algorithm can aid in the discovery of new genes with similar functions to a given list of genes already known to have closely related functions. biocViews: Microarray, Clustering Author: Gregory J. Hather , with contributions from Art B. Owen and Terence P. Speed Maintainer: Greg Hather source.ver: src/contrib/geneRecommender_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/geneRecommender_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/geneRecommender_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/geneRecommender_1.32.0.tgz vignettes: vignettes/geneRecommender/inst/doc/geneRecommender.pdf vignetteTitles: Using the geneRecommender Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geneRecommender/inst/doc/geneRecommender.R Package: GeneRegionScan Version: 1.16.0 Depends: methods, Biobase (>= 2.5.5), Biostrings Imports: Biobase (>= 2.5.5), affxparser, RColorBrewer, Biostrings Suggests: BSgenome, affy, AnnotationDbi License: GPL (>= 2) MD5sum: 60d60ca6484bfb5d8cbdeaacf43026e7 NeedsCompilation: no Title: GeneRegionScan Description: A package with focus on analysis of discrete regions of the genome. This package is useful for investigation of one or a few genes using Affymetrix data, since it will extract probe level data using the Affymetrix Power Tools application and wrap these data into a ProbeLevelSet. A ProbeLevelSet directly extends the expressionSet, but includes additional information about the sequence of each probe and the probe set it is derived from. The package includes a number of functions used for plotting these probe level data as a function of location along sequences of mRNA-strands. This can be used for analysis of variable splicing, and is especially well suited for use with exon-array data. biocViews: Microarray, DataImport, SNP, OneChannel, Visualization Author: Lasse Folkersen, Diego Diez Maintainer: Lasse Folkersen source.ver: src/contrib/GeneRegionScan_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneRegionScan_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneRegionScan_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneRegionScan_1.16.0.tgz vignettes: vignettes/GeneRegionScan/inst/doc/GeneRegionScan.pdf vignetteTitles: GeneRegionScan hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneRegionScan/inst/doc/GeneRegionScan.R Package: GeneSelectMMD Version: 2.4.0 Depends: R (>= 2.13.2), Biobase Imports: Biobase, MASS, graphics, stats, survival, limma Suggests: ALL License: GPL (>= 2) Archs: i386, x64 MD5sum: 7ad69f469bd4ba4df3f248dbabe7cb22 NeedsCompilation: yes Title: Gene selection based on the marginal distributions of gene profiles that characterized by a mixture of three-component multivariate distributions Description: Gene selection based on a mixture of marginal distributions biocViews: Bioinformatics, DifferentialExpression Author: Jarrett Morrow , Weiliang Qiu , Wenqing He , Xiaogang Wang , Ross Lazarus . Maintainer: Weiliang Qiu source.ver: src/contrib/GeneSelectMMD_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneSelectMMD_2.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneSelectMMD_2.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneSelectMMD_2.4.0.tgz vignettes: vignettes/GeneSelectMMD/inst/doc/GS207runTimesSim1k.pdf, vignettes/GeneSelectMMD/inst/doc/gsMMD.pdf vignetteTitles: GS207runTimesSim1k.pdf, Gene Selection based on a mixture of marginal distributions hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneSelectMMD/inst/doc/gsMMD.R Package: GeneSelector Version: 2.10.0 Depends: R (>= 2.5.1), methods, stats, Biobase Imports: multtest, siggenes, samr, limma Suggests: multtest, siggenes, samr, limma License: GPL (>= 2) Archs: i386, x64 MD5sum: e946a6afb3adea33986fd94b1322aa9a NeedsCompilation: yes Title: Stability and Aggregation of ranked gene lists Description: The term 'GeneSelector' refers to a filter selecting those genes which are consistently identified as differentially expressed using various statistical procedures. 'Selected' genes are those present at the top of the list in various ranking methods (currently 14). In addition, the stability of the findings can be taken into account in the final ranking by examining perturbed versions of the original data set, e.g. by leaving samples, swapping class labels, generating bootstrap replicates or adding noise. Given multiple ranked lists, one can use aggregation methods in order to find a synthesis. biocViews: Statistics, DifferentialExpression Author: Martin Slawski , Anne-Laure Boulesteix . Maintainer: Martin Slawski source.ver: src/contrib/GeneSelector_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneSelector_2.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneSelector_2.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneSelector_2.10.0.tgz vignettes: vignettes/GeneSelector/inst/doc/GeneSelector.pdf vignetteTitles: GeneSelector.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneSelector/inst/doc/GeneSelector.R Package: geNetClassifier Version: 1.0.2 Depends: R (>= 2.10.1), Biobase (>= 2.5.5), EBarrays, minet, methods Imports: e1071, ipred, graphics, BiocGenerics Suggests: leukemiasEset Enhances: RColorBrewer, igraph License: GPL (>= 2) MD5sum: b2d496ccf986aea43979bdf3caced4f0 NeedsCompilation: no Title: classify diseases and build associated gene networks using gene expression profiles Description: Comprehensive package to automatically train a multi-class SVM classifier based on gene expression data. Provides transparent selection of gene markers, their coexpression networks, and an interface to query the classifier. biocViews: Bioinformatics, Classification, Microarray, GeneExpression, Leukemia, Cancer Author: Sara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain. Maintainer: Sara Aibar URL: http://bioinfow.dep.usal.es/ source.ver: src/contrib/geNetClassifier_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/geNetClassifier_1.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/geNetClassifier_1.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/geNetClassifier_1.0.2.tgz vignettes: vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.pdf vignetteTitles: geNetClassifier-vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.R Package: GeneticsDesign Version: 1.28.0 Imports: gmodels, graphics, gtools (>= 2.4.0), mvtnorm, stats License: GPL-2 MD5sum: 28c084da4954e7909369c857a2cbd130 NeedsCompilation: no Title: Functions for designing genetics studies Description: This package contains functions useful for designing genetics studies, including power and sample-size calculations. biocViews: Genetics Author: Gregory Warnes David Duffy , Michael Man Weiliang Qiu Ross Lazarus Maintainer: The R Genetics Project source.ver: src/contrib/GeneticsDesign_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneticsDesign_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneticsDesign_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneticsDesign_1.28.0.tgz vignettes: vignettes/GeneticsDesign/inst/doc/GPC.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneticsDesign/inst/doc/GPC.R Package: GeneticsPed Version: 1.22.0 Depends: R (>= 2.4.0), gdata (>= 2.3.0), genetics (>= 1.3.0), MASS Suggests: RUnit, gtools License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: 8b5546c7763444c22042005c9a458b97 NeedsCompilation: yes Title: Pedigree and genetic relationship functions Description: Classes and methods for handling pedigree data. It also includes functions to calculate genetic relationship measures as relationship and inbreeding coefficients and other utilities. Note that package is not yet stable. Use it with care! biocViews: Genetics Author: Gregor Gorjanc and David A. Henderson , with code contributions by Brian Kinghorn and Andrew Percy (see file COPYING) Maintainer: David Henderson URL: http://rgenetics.org source.ver: src/contrib/GeneticsPed_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GeneticsPed_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GeneticsPed_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GeneticsPed_1.22.0.tgz vignettes: vignettes/GeneticsPed/inst/doc/geneticRelatedness.pdf, vignettes/GeneticsPed/inst/doc/pedigreeHandling.pdf, vignettes/GeneticsPed/inst/doc/quanGenAnimalModel.pdf vignetteTitles: Calculation of genetic relatedness/relationship between individuals in the pedigree, Pedigree handling, Quantitative genetic (animal) model example in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/GeneticsPed/inst/doc/geneticRelatedness.R, vignettes/GeneticsPed/inst/doc/pedigreeHandling.R, vignettes/GeneticsPed/inst/doc/quanGenAnimalModel.R Package: genoCN Version: 1.12.0 Imports: graphics, stats, utils License: GPL (>=2) Archs: i386, x64 MD5sum: 66ffd659d5d71a966ce8028683385a9e NeedsCompilation: yes Title: genotyping and copy number study tools Description: Simultaneous identification of copy number states and genotype calls for regions of either copy number variations or copy number aberrations biocViews: Microarray, Genetics Author: Wei Sun and ZhengZheng Tang Maintainer: Wei Sun source.ver: src/contrib/genoCN_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genoCN_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genoCN_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genoCN_1.12.0.tgz vignettes: vignettes/genoCN/inst/doc/genoCN.pdf vignetteTitles: add stuff hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genoCN/inst/doc/genoCN.R Package: GenomeGraphs Version: 1.20.0 Depends: R (>= 2.10), methods, biomaRt, grid License: Artistic-2.0 MD5sum: 78508ac6faf7012aedcfa6fdfeb2bc56 NeedsCompilation: no Title: Plotting genomic information from Ensembl Description: Genomic data analyses requires integrated visualization of known genomic information and new experimental data. GenomeGraphs uses the biomaRt package to perform live annotation queries to Ensembl and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data. Another strength of GenomeGraphs is to plot different data types such as array CGH, gene expression, sequencing and other data, together in one plot using the same genome coordinate system. biocViews: Visualization, Microarray Author: Steffen Durinck , James Bullard Maintainer: Steffen Durinck source.ver: src/contrib/GenomeGraphs_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GenomeGraphs_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GenomeGraphs_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GenomeGraphs_1.20.0.tgz vignettes: vignettes/GenomeGraphs/inst/doc/GenomeGraphs.pdf vignetteTitles: The GenomeGraphs users guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomeGraphs/inst/doc/GenomeGraphs.R dependsOnMe: Genominator, waveTiling suggestsMe: rMAT, triplex Package: genomeIntervals Version: 1.16.0 Depends: R (>= 2.15.0), methods, intervals (>= 0.14.0), BiocGenerics (>= 0.3.2) Imports: methods, Biobase License: Artistic-2.0 MD5sum: aa997b771413c637eb057e0e8cdc312a NeedsCompilation: no Title: Operations on genomic intervals Description: This package defines classes for representing genomic intervals and provides functions and methods for working with these. Note: The package provides the basic infrastructure for and is enhanced by the package 'girafe'. biocViews: DataImport, Infrastructure, Genetics Author: Julien Gagneur , Joern Toedling, Richard Bourgon, Nicolas Delhomme Maintainer: Julien Gagneur source.ver: src/contrib/genomeIntervals_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genomeIntervals_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genomeIntervals_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genomeIntervals_1.16.0.tgz vignettes: vignettes/genomeIntervals/inst/doc/genomeIntervals.pdf vignetteTitles: Overview of the genomeIntervals package. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genomeIntervals/inst/doc/genomeIntervals.R dependsOnMe: easyRNASeq, girafe Package: genomes Version: 2.6.0 Depends: R (>= 2.11), XML, RCurl, GenomicRanges, IRanges, Biostrings License: Artistic-2.0 MD5sum: 432f7d97533af7ae59aee09497b3288a NeedsCompilation: no Title: Genome sequencing project metadata Description: Collects genome sequencing project data from NCBI and the ENA. biocViews: Annotation, Genetics Author: Chris Stubben Maintainer: Chris Stubben source.ver: src/contrib/genomes_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genomes_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genomes_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genomes_2.6.0.tgz vignettes: vignettes/genomes/inst/doc/genome-tables.pdf vignetteTitles: Introduction to genome projects hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genomes/inst/doc/genome-tables.R Package: GenomicFeatures Version: 1.12.4 Depends: BiocGenerics (>= 0.1.0), IRanges (>= 1.17.13), GenomicRanges (>= 1.11.11), AnnotationDbi (>= 1.19.36) Imports: methods, DBI (>= 0.2-5), RSQLite (>= 0.8-1), BiocGenerics, IRanges, GenomicRanges, Biostrings (>= 2.23.2), rtracklayer (>= 1.15.1), biomaRt, RCurl, utils, Biobase (>= 2.15.1) Suggests: rtracklayer, biomaRt, org.Mm.eg.db, Biostrings, BSgenome, BSgenome.Hsapiens.UCSC.hg18 (>= 1.3.14), BSgenome.Hsapiens.UCSC.hg19 (>= 1.3.17), BSgenome.Celegans.UCSC.ce2, BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.17), mirbase.db, FDb.UCSC.tRNAs, TxDb.Hsapiens.UCSC.hg18.knownGene, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Dmelanogaster.UCSC.dm3.ensGene (>= 2.7.1), Rsamtools, pasillaBamSubset (>= 0.0.5), RUnit License: Artistic-2.0 MD5sum: 47de7e1e4d73bf0c8dfd4747c951bb9c NeedsCompilation: no Title: Tools for making and manipulating transcript centric annotations Description: A set of tools and methods for making and manipulating transcript centric annotations. With these tools the user can easily download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database (more sources will be supported in the future). This information is then stored in a local database that keeps track of the relationship between transcripts, exons, cds and genes. Flexible methods are provided for extracting the desired features in a convenient format. biocViews: Genetics, Infrastructure, Annotation, HighThroughputSequencing Author: M. Carlson, H. Pages, P. Aboyoun, S. Falcon, M. Morgan, D. Sarkar, M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicFeatures_1.12.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/GenomicFeatures_1.12.4.zip win64.binary.ver: bin/windows64/contrib/2.16/GenomicFeatures_1.12.4.zip mac.binary.ver: bin/macosx/contrib/2.16/GenomicFeatures_1.12.4.tgz vignettes: vignettes/GenomicFeatures/inst/doc/GenomicFeatures.pdf vignetteTitles: Making and Utilizing TranscriptDb Objects hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomicFeatures/inst/doc/GenomicFeatures.R dependsOnMe: ChIPpeakAnno, OrganismDbi, SplicingGraphs importsMe: biovizBase, casper, ChIPpeakAnno, ggbio, gmapR, Gviz, HTSeqGenie, MEDIPS, methyAnalysis, QuasR, SplicingGraphs, VariantAnnotation, VariantTools suggestsMe: biomvRCNS, Biostrings, chipseq, DEXSeq, easyRNASeq, GenomicRanges, Gviz, HTSeqGenie, MiRaGE, RIPSeeker, Rsamtools, ShortRead Package: GenomicRanges Version: 1.12.5 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.5.4), IRanges (>= 1.17.33) Imports: methods, utils, stats, BiocGenerics, IRanges LinkingTo: IRanges Suggests: AnnotationDbi (>= 1.21.1), Biostrings (>= 2.25.3), Rsamtools (>= 1.11.24), BSgenome, rtracklayer, GenomicFeatures, VariantAnnotation, edgeR, DESeq, DEXSeq, EatonEtAlChIPseq (>= 0.0.3), leeBamViews, pasilla, pasillaBamSubset, org.Sc.sgd.db, TxDb.Dmelanogaster.UCSC.dm3.ensGene, seqnames.db, BSgenome.Scerevisiae.UCSC.sacCer2, BSgenome.Dmelanogaster.UCSC.dm3, RUnit, digest License: Artistic-2.0 Archs: i386, x64 MD5sum: d1dda187189875ae3f13e0cd8e061103 NeedsCompilation: yes Title: Representation and manipulation of genomic intervals Description: The ability to efficiently store genomic annotations and alignments is playing a central role when it comes to analyze high-throughput sequencing data (a.k.a. NGS data). The package defines general purpose containers for storing genomic intervals as well as more specialized containers for storing alignments against a reference genome. biocViews: Genetics, Sequencing, HighThroughputSequencing, Annotation Author: P. Aboyoun, H. Pages and M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicRanges_1.12.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/GenomicRanges_1.12.5.zip win64.binary.ver: bin/windows64/contrib/2.16/GenomicRanges_1.12.5.zip mac.binary.ver: bin/macosx/contrib/2.16/GenomicRanges_1.12.5.tgz vignettes: vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.pdf, vignettes/GenomicRanges/inst/doc/GenomicRangesUseCases.pdf, vignettes/GenomicRanges/inst/doc/OverlapEncodings.pdf, vignettes/GenomicRanges/inst/doc/summarizeOverlaps-modes.pdf, vignettes/GenomicRanges/inst/doc/summarizeOverlaps.pdf vignetteTitles: An Introduction to GenomicRanges, GenomicRanges Use Cases, Overlap encodings, summarizeOverlaps-modes.pdf, Overview of summarizeOverlaps hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomicRanges/inst/doc/GenomicRangesUseCases.R, vignettes/GenomicRanges/inst/doc/OverlapEncodings.R, vignettes/GenomicRanges/inst/doc/summarizeOverlaps.R dependsOnMe: annmap, biomvRCNS, BiSeq, BSgenome, bsseq, bumphunter, casper, chimera, chipseq, cn.mops, CSAR, DASiR, deepSNV, DESeq2, DiffBind, easyRNASeq, ensemblVEP, epigenomix, exomeCopy, fastseg, genomes, GenomicFeatures, genoset, GGtools, gmapR, gwascat, HiTC, htSeqTools, minfi, PING, QuasR, Rcade, Repitools, RIPSeeker, Rsamtools, rSFFreader, RSVSim, rtracklayer, segmentSeq, seqbias, ShortRead, SomatiCA, SplicingGraphs, VariantAnnotation, VariantTools importsMe: AnnotationHub, ArrayExpressHTS, biovizBase, BiSeq, CAGEr, chipseq, ChIPseqR, copynumber, DESeq2, DEXSeq, epigenomix, FunciSNP, GenomicFeatures, genoset, ggbio, gmapR, Gviz, HTSeqGenie, HTSFilter, MEDIPS, methyAnalysis, MethylSeekR, MinimumDistance, NarrowPeaks, nucleR, oligoClasses, PICS, prebs, QuasR, Repitools, rnaSeqMap, Rsamtools, rSFFreader, rtracklayer, segmentSeq, ShortRead, SNPchip, SomatiCA, SplicingGraphs, triplex, VanillaICE, VariantTools, waveTiling suggestsMe: BiocGenerics, IRanges, methylumi, MiRaGE, NarrowPeaks, Repitools Package: Genominator Version: 1.14.0 Depends: R (>= 2.10), methods, RSQLite, DBI (>= 0.2-5), BiocGenerics (>= 0.1.0), IRanges, GenomeGraphs Imports: graphics, stats, utils Suggests: biomaRt, ShortRead, yeastRNASeq License: Artistic-2.0 MD5sum: 49548d6b1f7cf19901f4416e81b5afa5 NeedsCompilation: no Title: Analyze, manage and store genomic data Description: Tools for storing, accessing, analyzing and visualizing genomic data. biocViews: Infrastructure Author: James Bullard, Kasper Daniel Hansen Maintainer: James Bullard source.ver: src/contrib/Genominator_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Genominator_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Genominator_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Genominator_1.14.0.tgz vignettes: vignettes/Genominator/inst/doc/Genominator.pdf, vignettes/Genominator/inst/doc/plotting.pdf, vignettes/Genominator/inst/doc/withShortRead.pdf vignetteTitles: The Genominator User Guide, Plotting with Genominator, Working with the ShortRead Package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Genominator/inst/doc/Genominator.R, vignettes/Genominator/inst/doc/plotting.R, vignettes/Genominator/inst/doc/withShortRead.R suggestsMe: oneChannelGUI Package: genoset Version: 1.12.0 Depends: R (>= 2.10), BiocGenerics (>= 0.1.6), Biobase (>= 2.15.1), IRanges (>= 1.13.5), GenomicRanges Imports: methods, graphics, GenomicRanges Suggests: RUnit, DNAcopy, stats Enhances: parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 470eb9acceebe1d06d4cecc84d9f681e NeedsCompilation: yes Title: Provides classes similar to ExpressionSet for copy number analysis Description: Load, manipulate, and plot copynumber and BAF data. GenoSet class extends eSet by adding a "locData" slot for a RangedData or GRanegs object. This object contains feature genome location data and provides for efficient subsetting on genome location. CNSet and BAFSet extend GenoSet and require assayData matrices for Copy Number (cn) or Log-R Ratio (lrr) and B-Allele Frequency (baf) data. Implements and provides convenience functions for processing of copy number and B-Allele Frequency data. biocViews: Infrastructure, DataRepresentation, Microarray, SNP, CopyNumberVariants Author: Peter M. Haverty Maintainer: Peter M. Haverty source.ver: src/contrib/genoset_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/genoset_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/genoset_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/genoset_1.12.0.tgz vignettes: vignettes/genoset/inst/doc/genoset.pdf vignetteTitles: genoset hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genoset/inst/doc/genoset.R dependsOnMe: VegaMC importsMe: methyAnalysis Package: GEOmetadb Version: 1.20.0 Depends: GEOquery,RSQLite License: Artistic-2.0 MD5sum: 29370eb1a68f8fe07452984368c7d052 NeedsCompilation: no Title: A compilation of metadata from NCBI GEO Description: The NCBI Gene Expression Omnibus (GEO) represents the largest public repository of microarray data. However, finding data of interest can be challenging using current tools. GEOmetadb is an attempt to make access to the metadata associated with samples, platforms, and datasets much more feasible. This is accomplished by parsing all the NCBI GEO metadata into a SQLite database that can be stored and queried locally. GEOmetadb is simply a thin wrapper around the SQLite database along with associated documentation. Finally, the SQLite database is updated regularly as new data is added to GEO and can be downloaded at will for the most up-to-date metadata. GEOmetadb paper: http://bioinformatics.oxfordjournals.org/cgi/content/short/24/23/2798 . biocViews: Infrastructure Author: Jack Zhu and Sean Davis Maintainer: Jack Zhu URL: http://gbnci.abcc.ncifcrf.gov/geo/ source.ver: src/contrib/GEOmetadb_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GEOmetadb_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GEOmetadb_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GEOmetadb_1.20.0.tgz vignettes: vignettes/GEOmetadb/inst/doc/GEOmetadb_diagram.pdf, vignettes/GEOmetadb/inst/doc/GEOmetadb.pdf vignetteTitles: GEOmetadb_diagram.pdf, GEOmetadb hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOmetadb/inst/doc/GEOmetadb.R Package: GEOquery Version: 2.26.2 Depends: methods, Biobase Imports: XML, RCurl Suggests: limma License: GPL-2 MD5sum: 1857ca45193e131b332a169fb1efd241 NeedsCompilation: no Title: Get data from NCBI Gene Expression Omnibus (GEO) Description: The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor. biocViews: Microarray, DataImport, OneChannel, TwoChannel, SAGE Author: Sean Davis Maintainer: Sean Davis URL: http://watson.nci.nih.gov/~sdavis source.ver: src/contrib/GEOquery_2.26.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/GEOquery_2.26.2.zip win64.binary.ver: bin/windows64/contrib/2.16/GEOquery_2.26.2.zip mac.binary.ver: bin/macosx/contrib/2.16/GEOquery_2.26.2.tgz vignettes: vignettes/GEOquery/inst/doc/GEOquery.pdf vignetteTitles: GEOquery hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOquery/inst/doc/GEOquery.R dependsOnMe: DrugVsDisease importsMe: ChIPXpress, SRAdb, virtualArray suggestsMe: dyebias, PGSEA Package: GEOsubmission Version: 1.12.0 Imports: affy, Biobase, utils License: GPL (>= 2) MD5sum: 6d9bcf042ca17ab781b6a5951b5c8d4c NeedsCompilation: no Title: Prepares microarray data for submission to GEO Description: Helps to easily submit a microarray dataset and the associated sample information to GEO by preparing a single file for upload (direct deposit). biocViews: Microarray Author: Alexandre Kuhn Maintainer: Alexandre Kuhn source.ver: src/contrib/GEOsubmission_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GEOsubmission_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GEOsubmission_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GEOsubmission_1.12.0.tgz vignettes: vignettes/GEOsubmission/inst/doc/GEOsubmission.pdf vignetteTitles: GEOsubmission Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOsubmission/inst/doc/GEOsubmission.R Package: GEWIST Version: 1.4.0 Depends: R (>= 2.10), car License: GPL-2 MD5sum: d31cee9f14fb1dd6a356e17b88b81d4a NeedsCompilation: no Title: Gene Environment Wide Interaction Search Threshold Description: This 'GEWIST' package provides statistical tools to efficiently optimize SNP prioritization for gene-gene and gene-environment interactions. biocViews: Bioinformatics, MultipleComparisons, BiologicalDomains, Genetics Author: Wei Q. Deng, Guillaume Pare Maintainer: Wei Q. Deng source.ver: src/contrib/GEWIST_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GEWIST_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GEWIST_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GEWIST_1.4.0.tgz vignettes: vignettes/GEWIST/inst/doc/GEWIST.pdf vignetteTitles: GEWIST.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEWIST/inst/doc/GEWIST.R Package: GGBase Version: 3.22.0 Depends: R (>= 2.14), methods, snpStats Imports: limma, genefilter, Biobase, BiocGenerics, Matrix, AnnotationDbi License: Artistic-2.0 MD5sum: a2a661bc3e9b12e845c2d38b064d4ec9 NeedsCompilation: no Title: GGBase infrastructure for genetics of gene expression package GGtools Description: infrastructure biocViews: Genetics, Infrastructure Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/GGBase_3.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GGBase_3.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GGBase_3.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GGBase_3.22.0.tgz vignettes: vignettes/GGBase/inst/doc/ggbase.pdf vignetteTitles: GGBase -- infrastructure for GGtools,, genetics of gene expression hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GGBase/inst/doc/ggbase.R dependsOnMe: GGtools importsMe: qpgraph Package: ggbio Version: 1.8.8 Depends: methods, ggplot2 (>= 0.9.2) Imports: methods, biovizBase(>= 1.7.8), reshape2, gtable, ggplot2(>= 0.9.2), BiocGenerics, Biobase, IRanges, GenomicRanges, GenomicFeatures, Rsamtools, BSgenome, gridExtra, scales, plyr, VariantAnnotation, Hmisc, rtracklayer Suggests: BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, affyPLM, chipseq, TxDb.Mmusculus.UCSC.mm9.knownGene, knitr License: Artistic-2.0 MD5sum: e47162113a15f8c91dbae6398890cdec NeedsCompilation: no Title: Visualization tools for genomic data. Description: The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries. biocViews: Infrastructure, Visualization, Bioinformatics Author: Tengfei Yin, Dianne Cook, Michael Lawrence Maintainer: Tengfei Yin URL: http://tengfei.github.com/ggbio/ source.ver: src/contrib/ggbio_1.8.8.tar.gz win.binary.ver: bin/windows/contrib/2.16/ggbio_1.8.8.zip win64.binary.ver: bin/windows64/contrib/2.16/ggbio_1.8.8.zip mac.binary.ver: bin/macosx/contrib/2.16/ggbio_1.8.8.tgz vignettes: vignettes/ggbio/inst/doc/ggbio.pdf vignetteTitles: Part 0: Introduction and quick start hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ggbio/inst/doc/ggbio.R, vignettes/ggbio/inst/doc/p0_ggbio.R, vignettes/ggbio/inst/doc/p1_tracks.R, vignettes/ggbio/inst/doc/p2_ideogram.R, vignettes/ggbio/inst/doc/p3_overview.R, vignettes/ggbio/inst/doc/p4_txdb.R, vignettes/ggbio/inst/doc/p5_case.R importsMe: ReportingTools suggestsMe: gwascat, ReportingTools Package: GGtools Version: 4.8.0 Depends: R (>= 2.14), stats4, GGBase (>= 3.19.7), IRanges, GenomicRanges, Rsamtools Imports: methods, utils, stats, BiocGenerics, snpStats, ff, AnnotationDbi, Biobase, bit, VariantAnnotation Suggests: GGdata, illuminaHumanv1.db, SNPlocs.Hsapiens.dbSNP.20120608 Enhances: MatrixEQTL License: Artistic-2.0 MD5sum: 60b1a2b3618600b8c585a3a3f1614a89 NeedsCompilation: no Title: software and data for analyses in genetics of gene expression Description: software and data for analyses in genetics of gene expression and/or DNA methylation biocViews: Genetics, GeneExpression, GeneticVariability, SNP Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/GGtools_4.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GGtools_4.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GGtools_4.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GGtools_4.8.0.tgz vignettes: vignettes/GGtools/inst/doc/GGtools_2012.pdf vignetteTitles: GGtools 2012: efficient tools for eQTL discovery hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GGtools/inst/doc/GGtools_2012.R Package: girafe Version: 1.12.0 Depends: R (>= 2.10.0), methods, IRanges (>= 1.3.53), Rsamtools, ShortRead (>= 1.3.21), intervals (>= 0.13.1), genomeIntervals (>= 1.7.3), grid Imports: methods, Biobase, Biostrings, BSgenome, graphics, grDevices, stats, utils, IRanges Suggests: MASS, org.Mm.eg.db, RColorBrewer Enhances: genomeIntervals License: Artistic-2.0 Archs: i386, x64 MD5sum: c0342f223015b8fcb2f4af8d9b373e4f NeedsCompilation: yes Title: Genome Intervals and Read Alignments for Functional Exploration Description: The package 'girafe' deals with the genome-level representation of aligned reads from next-generation sequencing data. It contains an object class for enabling a detailed description of genome intervals with aligned reads and functions for comparing, visualising, exporting and working with such intervals and the aligned reads. As such, the package interacts with and provides a link between the packages ShortRead, IRanges and genomeIntervals. biocViews: Sequencing, HighThroughputSequencing Author: Joern Toedling, with contributions from Constance Ciaudo, Olivier Voinnet, Edith Heard, Emmanuel Barillot, and Wolfgang Huber Maintainer: J. Toedling source.ver: src/contrib/girafe_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/girafe_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/girafe_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/girafe_1.12.0.tgz vignettes: vignettes/girafe/inst/doc/girafe.pdf vignetteTitles: Genome intervals and read alignments for functional exploration hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/girafe/inst/doc/girafe.R Package: GLAD Version: 2.24.0 Depends: R (>= 2.10) Suggests: aws, tcltk License: GPL-2 Archs: i386, x64 MD5sum: f8ed7545e15a2243e5a9f4cd992b6850 NeedsCompilation: yes Title: Gain and Loss Analysis of DNA Description: Analysis of array CGH data : detection of breakpoints in genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified. biocViews: Microarray, CopyNumberVariants Author: Philippe Hupe Maintainer: Philippe Hupe URL: http://bioinfo.curie.fr SystemRequirements: gsl. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. source.ver: src/contrib/GLAD_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GLAD_2.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GLAD_2.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GLAD_2.24.0.tgz vignettes: vignettes/GLAD/inst/doc/GLAD.pdf vignetteTitles: GLAD hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GLAD/inst/doc/GLAD.R dependsOnMe: ITALICS, MANOR importsMe: ITALICS, MANOR, snapCGH suggestsMe: ADaCGH2 Package: GlobalAncova Version: 3.28.0 Depends: methods, corpcor, globaltest Imports: annotate, AnnotationDbi Suggests: Biobase, annotate, GO.db, KEGG.db, golubEsets, hu6800.db, vsn, GSEABase, Rgraphviz License: GPL (>= 2) Archs: i386, x64 MD5sum: 0a1d8652c7a0348de45b1fef1e6a3978 NeedsCompilation: yes Title: Calculates a global test for differential gene expression between groups Description: We give the following arguments in support of the GlobalAncova approach: After appropriate normalisation, gene-expression-data appear rather symmetrical and outliers are no real problem, so least squares should be rather robust. ANCOVA with interaction yields saturated data modelling e.g. different means per group and gene. Covariate adjustment can help to correct for possible selection bias. Variance homogeneity and uncorrelated residuals cannot be expected. Application of ordinary least squares gives unbiased, but no longer optimal estimates (Gauss-Markov-Aitken). Therefore, using the classical F-test is inappropriate, due to correlation. The test statistic however mirrors deviations from the null hypothesis. In combination with a permutation approach, empirical significance levels can be approximated. Alternatively, an approximation yields asymptotic p-values. This work was supported by the NGFN grant 01 GR 0459, BMBF, Germany. biocViews: Microarray, OneChannel, Bioinformatics, DifferentialExpression, Pathways Author: U. Mansmann, R. Meister, M. Hummel, R. Scheufele, with contributions from S. Knueppel Maintainer: Manuela Hummel source.ver: src/contrib/GlobalAncova_3.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GlobalAncova_3.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GlobalAncova_3.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GlobalAncova_3.28.0.tgz vignettes: vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.pdf, vignettes/GlobalAncova/inst/doc/GlobalAncova.pdf vignetteTitles: GlobalAncovaDecomp.pdf, GlobalAncova.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.R, vignettes/GlobalAncova/inst/doc/GlobalAncova.R Package: globaltest Version: 5.14.0 Depends: methods Imports: Biobase, survival, AnnotationDbi, annotate, multtest, graphics Suggests: vsn, golubEsets, KEGG.db, hu6800.db, Rgraphviz, GO.db, lungExpression, org.Hs.eg.db, annotate, Biobase, survival, GSEABase, penalized, gss, MASS, boot, rpart License: GPL (>= 2) MD5sum: 1dc0bd6ff9c59d755192a85fc2246196 NeedsCompilation: no Title: Testing groups of covariates/features for association with a response variable, with applications to gene set testing Description: The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms. biocViews: Microarray, OneChannel, Bioinformatics, DifferentialExpression, GO, Pathways Author: Jelle Goeman and Jan Oosting, with contributions by Livio Finos and Aldo Solari Maintainer: Jelle Goeman URL: http://www.msbi.nl/goeman source.ver: src/contrib/globaltest_5.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/globaltest_5.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/globaltest_5.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/globaltest_5.14.0.tgz vignettes: vignettes/globaltest/inst/doc/GlobalTest.pdf vignetteTitles: Global Test hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/globaltest/inst/doc/GlobalTest.R dependsOnMe: GlobalAncova importsMe: SIM suggestsMe: topGO Package: gmapR Version: 1.2.0 Depends: R (>= 2.15.0), methods, GenomicRanges Imports: IRanges, Rsamtools (>= 1.7.4), rtracklayer (>= 1.17.15), GenomicRanges, GenomicFeatures, Biostrings, VariantAnnotation, tools, Biobase, BSgenome Suggests: RUnit, BSgenome.Dmelanogaster.UCSC.dm3, BSgenome.Scerevisiae.UCSC.sacCer3, VariantAnnotation, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, BSgenome.Hsapiens.UCSC.hg19, LungCancerLines License: Artistic-2.0 MD5sum: def4a9ea844f7ef34fd25daa28b53999 NeedsCompilation: yes Title: Provides convenience methods to work with GMAP and GSNAP from within R Description: GSNAP and GMAP are a pair of tools to align short-read data written by Tom Wu. This package provides convenience methods to work with GMAP and GSNAP from within R. In addition, it provides methods to tally alignment results on a per-nucleotide basis using the bam_tally tool. Author: Cory Barr, Thomas Wu, Michael Lawrence Maintainer: Michael Lawrence source.ver: src/contrib/gmapR_1.2.0.tar.gz vignettes: vignettes/gmapR/inst/doc/gmapR.pdf vignetteTitles: gmapR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gmapR/inst/doc/gmapR.R dependsOnMe: HTSeqGenie importsMe: VariantTools Package: GOFunction Version: 1.6.0 Depends: R (>= 2.11.0), methods, Biobase (>= 2.8.0), graph (>= 1.26.0), Rgraphviz (>= 1.26.0), GO.db (>= 2.4.1), AnnotationDbi (>= 1.10.2), SparseM (>= 0.85) Imports: methods, Biobase, graph, Rgraphviz, GO.db, AnnotationDbi, SparseM License: GPL (>= 2) MD5sum: d42add1c3e64c0cfb4ea743f8efb7a8a NeedsCompilation: no Title: GO-function: deriving biologcially relevant functions from statistically significant functions Description: The GO-function package provides a tool to address the redundancy that result from the GO structure or multiple annotation genes and derive biologically relevant functions from the statistically significant functions based on some intuitive assumption and statistical testing. biocViews: GO, Pathways, Microarray, GeneSetEnrichment Author: Jing Wang Maintainer: Zheng Guo source.ver: src/contrib/GOFunction_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GOFunction_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GOFunction_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GOFunction_1.6.0.tgz vignettes: vignettes/GOFunction/inst/doc/GOFunction.pdf vignetteTitles: GO-function hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOFunction/inst/doc/GOFunction.R Package: goProfiles Version: 1.22.0 Depends: Biobase, AnnotationDbi, GO.db Suggests: org.Hs.eg.db License: GPL-2 MD5sum: 057a5a03ede559552b5e5ff72e881fe5 NeedsCompilation: no Title: goProfiles: an R package for the statistical analysis of functional profiles Description: The package implements methods to compare lists of genes based on comparing the corresponding 'functional profiles'. biocViews: Microarray, GO Author: Alex Sanchez, Jordi Ocana and Miquel Salicru Maintainer: Alex Sanchez source.ver: src/contrib/goProfiles_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/goProfiles_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/goProfiles_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/goProfiles_1.22.0.tgz vignettes: vignettes/goProfiles/inst/doc/goProfiles.pdf vignetteTitles: goProfiles Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/goProfiles/inst/doc/goProfiles.R Package: GOSemSim Version: 1.18.0 Depends: R (>= 2.10), Rcpp Imports: methods, AnnotationDbi, GO.db, org.Hs.eg.db LinkingTo: Rcpp Suggests: DOSE, clusterProfiler, BiocInstaller License: GPL-2 Archs: i386, x64 MD5sum: aca154e218b31410388403a6b866382f NeedsCompilation: yes Title: GO-terms Semantic Similarity Measures Description: Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for estimating GO semantic similarities. Support many species, including Anopheles, Arabidopsis, Bovine, Canine, Chicken, Chimp, Coelicolor, E coli strain K12 and Sakai, Fly, Human, Malaria, Mouse, Pig, Rhesus, Rat, Worm, Xenopus, Yeast, and Zebrafish. biocViews: GO, Clustering, Pathways, NetworkAnalysis Author: Guangchuang Yu Maintainer: Guangchuang Yu URL: http://bioinformatics.oxfordjournals.org/content/26/7/976.full source.ver: src/contrib/GOSemSim_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GOSemSim_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GOSemSim_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GOSemSim_1.18.0.tgz vignettes: vignettes/GOSemSim/inst/doc/GOSemSim.pdf vignetteTitles: An introduction to GOSemSim hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOSemSim/inst/doc/GOSemSim.R importsMe: DOSE suggestsMe: clusterProfiler, ReactomePA Package: goseq Version: 1.12.0 Depends: R (>= 2.11.0), BiasedUrn, geneLenDataBase Imports: mgcv, graphics, stats, utils, AnnotationDbi Suggests: GO.db, edgeR, org.Hs.eg.db, rtracklayer License: LGPL (>= 2) MD5sum: 1a7d1876d99e35fed7fcaee71783e016 NeedsCompilation: no Title: Gene Ontology analyser for RNA-seq and other length biased data Description: Detects Gene Ontology and/or other user defined categories which are over/under represented in RNA-seq data biocViews: HighThroughputSequencingData, GO, GeneExpression, Transcription, RNAseq Author: Matthew Young Maintainer: Matthew Young , Nadia Davidson source.ver: src/contrib/goseq_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/goseq_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/goseq_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/goseq_1.12.0.tgz vignettes: vignettes/goseq/inst/doc/goseq.pdf vignetteTitles: goseq User's Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/goseq/inst/doc/goseq.R suggestsMe: oneChannelGUI Package: GOstats Version: 2.26.0 Depends: R (>= 2.10), Biobase (>= 1.15.29), Category (>= 2.3.26), graph Imports: AnnotationDbi (>= 0.0.89), Biobase (>= 1.15.29), Category (>= 2.3.26), GO.db (>= 1.13.0), RBGL, annotate (>= 1.13.2), graph (>= 1.15.15), methods, stats , AnnotationForge Suggests: hgu95av2.db (>= 1.13.0), ALL, GO.db (>= 1.13.0), annotate, multtest, genefilter, RColorBrewer, Rgraphviz, xtable, SparseM, GSEABase, geneplotter, org.Hs.eg.db, RUnit, BiocGenerics License: Artistic-2.0 MD5sum: 627baad79cc71c8be78fab486af83478 NeedsCompilation: no Title: Tools for manipulating GO and microarrays. Description: A set of tools for interacting with GO and microarray data. A variety of basic manipulation tools for graphs, hypothesis testing and other simple calculations. biocViews: Bioinformatics, Annotation, GO, MultipleComparisons Author: R. Gentleman and S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GOstats_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GOstats_2.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GOstats_2.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GOstats_2.26.0.tgz vignettes: vignettes/GOstats/inst/doc/GOstatsForUnsupportedOrganisms.pdf, vignettes/GOstats/inst/doc/GOstatsHyperG.pdf, vignettes/GOstats/inst/doc/GOvis.pdf vignetteTitles: Hypergeometric tests for less common model organisms, Hypergeometric Tests Using GOstats, Visualizing Data Using GOstats hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOstats/inst/doc/GOstatsHyperG.R, vignettes/GOstats/inst/doc/GOvis.R dependsOnMe: attract, MineICA importsMe: affycoretools, attract, categoryCompare suggestsMe: BiocCaseStudies, Category, eisa, GSEAlm, HTSanalyzeR, MineICA, MLP, MmPalateMiRNA, oneChannelGUI, phenoDist, safe Package: goTools Version: 1.34.0 Depends: GO.db Imports: AnnotationDbi, GO.db, graphics, grDevices Suggests: hgu133a.db License: GPL-2 MD5sum: c8c1a62556555fa89816f4b097cbce1c NeedsCompilation: no Title: Functions for Gene Ontology database Description: Wraper functions for description/comparison of oligo ID list using Gene Ontology database biocViews: Microarray,GO,Visualization Author: Yee Hwa (Jean) Yang , Agnes Paquet Maintainer: Agnes Paquet source.ver: src/contrib/goTools_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/goTools_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/goTools_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/goTools_1.34.0.tgz vignettes: vignettes/goTools/inst/doc/goTools.pdf vignetteTitles: goTools overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/goTools/inst/doc/goTools.R Package: gpls Version: 1.32.0 Imports: stats Suggests: MASS License: Artistic-2.0 MD5sum: d7a6d3389d377fce4da1578f61c4800a NeedsCompilation: no Title: Classification using generalized partial least squares Description: Classification using generalized partial least squares for two-group and multi-group (more than 2 group) classification. biocViews: Bioinformatics, Classification, Microarray Author: Beiying Ding Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/gpls_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gpls_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gpls_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gpls_1.32.0.tgz vignettes: vignettes/gpls/inst/doc/gpls.pdf vignetteTitles: gpls Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gpls/inst/doc/gpls.R suggestsMe: MCRestimate, MLInterfaces Package: gprege Version: 1.4.1 Depends: R (>= 2.8.0), gptk Suggests: spam License: AGPL-3 MD5sum: 298b92e78621c55e44637a1ddd2b1ff1 NeedsCompilation: no Title: Gaussian Process Ranking and Estimation of Gene Expression time-series Description: The gprege package implements the methodology described in Kalaitzis & Lawrence (2011) "A simple approach to ranking differentially expressed gene expression time-courses through Gaussian process regression". The software fits two GPs with the an RBF (+ noise diagonal) kernel on each profile. One GP kernel is initialised wih a short lengthscale hyperparameter, signal variance as the observed variance and a zero noise variance. It is optimised via scaled conjugate gradients (netlab). A second GP has fixed hyperparameters: zero inverse-width, zero signal variance and noise variance as the observed variance. The log-ratio of marginal likelihoods of the two hypotheses acts as a score of differential expression for the profile. Comparison via ROC curves is performed against BATS (Angelini et.al, 2007). A detailed discussion of the ranking approach and dataset used can be found in the paper (http://www.biomedcentral.com/1471-2105/12/180). biocViews: Microarray, Preprocessing, Bioinformatics, DifferentialExpression, TimeCourse Author: Alfredo Kalaitzis Maintainer: Alfredo Kalaitzis source.ver: src/contrib/gprege_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/gprege_1.4.1.zip win64.binary.ver: bin/windows64/contrib/2.16/gprege_1.4.1.zip mac.binary.ver: bin/macosx/contrib/2.16/gprege_1.4.1.tgz vignettes: vignettes/gprege/inst/doc/gprege_quick.pdf vignetteTitles: gprege Quick Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gprege/inst/doc/gprege_quick.R Package: graph Version: 1.38.3 Depends: R (>= 2.10), methods Imports: methods, stats, stats4, tools, utils, BiocGenerics (>= 0.1.11) Suggests: SparseM (>= 0.36), XML, RBGL, RUnit, cluster Enhances: Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: 237b92c69963afd5e530a1dda21ea734 NeedsCompilation: yes Title: graph: A package to handle graph data structures Description: A package that implements some simple graph handling capabilities. biocViews: GraphsAndNetworks Author: R. Gentleman, Elizabeth Whalen, W. Huber, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/graph_1.38.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/graph_1.38.3.zip win64.binary.ver: bin/windows64/contrib/2.16/graph_1.38.3.zip mac.binary.ver: bin/macosx/contrib/2.16/graph_1.38.3.tgz vignettes: vignettes/graph/inst/doc/clusterGraph.pdf, vignettes/graph/inst/doc/graphAttributes.pdf, vignettes/graph/inst/doc/GraphClass.pdf, vignettes/graph/inst/doc/graph.pdf, vignettes/graph/inst/doc/MultiGraphClass.pdf vignetteTitles: clusterGraph and distGraph, Attributes for Graph Objects, Graph Design, Graph, graphBAM and MultiGraph classes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/graph/inst/doc/clusterGraph.R, vignettes/graph/inst/doc/graphAttributes.R, vignettes/graph/inst/doc/GraphClass.R, vignettes/graph/inst/doc/graph.R, vignettes/graph/inst/doc/MultiGraphClass.R dependsOnMe: apComplex, biocGraph, BioMVCClass, BioNet, CellNOptR, clipper, CNORfeeder, ddgraph, flowClust, flowWorkspace, gaggle, GeneNetworkBuilder, GOFunction, GOstats, GraphAT, graphite, GSEABase, gwascat, hyperdraw, hypergraph, KEGGgraph, maigesPack, MineICA, NCIgraph, nem, netresponse, pathRender, pkgDepTools, RbcBook1, RBGL, RBioinf, RCytoscape, Rgraphviz, ROntoTools, RpsiXML, Rtreemix, SRAdb, topGO importsMe: biocGraph, biocViews, CAMERA, Category, categoryCompare, DEGraph, flowCore, flowUtils, flowWorkspace, gage, GeneNetworkBuilder, GOFunction, GOstats, GraphAT, graphite, GSEABase, HTSanalyzeR, KEGGgraph, keggorthology, NCIgraph, nem, OrganismDbi, pathview, PCpheno, pkgDepTools, ppiStats, qpgraph, RchyOptimyx, Rgraphviz, rsbml, Rtreemix, SplicingGraphs, Streamer, topGO, VariantTools suggestsMe: AnnotationDbi, BiocCaseStudies, Category, categoryCompare, DEGraph, EBcoexpress, ecolitk, GeneAnswers, MmPalateMiRNA, rBiopaxParser, SPIA Package: GraphAlignment Version: 1.24.0 License: file LICENSE License_restricts_use: yes Archs: i386, x64 MD5sum: 5bfb3e89e57142fec26d058da96fa779 NeedsCompilation: yes Title: GraphAlignment Description: Graph alignment is an extension package for the R programming environment which provides functions for finding an alignment between two networks based on link and node similarity scores. (J. Berg and M. Laessig, "Cross-species analysis of biological networks by Bayesian alignment", PNAS 103 (29), 10967-10972 (2006)) biocViews: GraphsAndNetworks, NetworkAnalysis Author: Joern P. Meier , Michal Kolar, Ville Mustonen, Michael Laessig, and Johannes Berg. Maintainer: Joern P. Meier URL: http://www.thp.uni-koeln.de/~berg/GraphAlignment/ source.ver: src/contrib/GraphAlignment_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GraphAlignment_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GraphAlignment_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GraphAlignment_1.24.0.tgz vignettes: vignettes/GraphAlignment/inst/doc/align_principle2b1.pdf, vignettes/GraphAlignment/inst/doc/align_principle2c1.pdf, vignettes/GraphAlignment/inst/doc/align_principle_short1.pdf, vignettes/GraphAlignment/inst/doc/a.pdf, vignettes/GraphAlignment/inst/doc/binning-01a.pdf, vignettes/GraphAlignment/inst/doc/GraphAlignment.pdf vignetteTitles: align_principle2b1.pdf, align_principle2c1.pdf, align_principle_short1.pdf, a.pdf, binning-01a.pdf, GraphAlignment hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/GraphAlignment/inst/doc/GraphAlignment.R Package: GraphAT Version: 1.32.0 Depends: R (>= 2.10), graph, methods Imports: graph, MCMCpack, methods, stats License: LGPL MD5sum: 31e8a4f8cfcaccafdd155d32bdc06b65 NeedsCompilation: no Title: Graph Theoretic Association Tests Description: Functions and data used in Balasubramanian, et al. (2004) biocViews: NetworkAnalysis, GraphsAndNetworks Author: R. Balasubramanian, T. LaFramboise, D. Scholtens Maintainer: Thomas LaFramboise source.ver: src/contrib/GraphAT_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GraphAT_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GraphAT_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GraphAT_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: graphite Version: 1.6.0 Depends: R (>= 2.10), graph Imports: AnnotationDbi, graph, graphics, methods, org.Hs.eg.db, stats, utils Suggests: DEGraph (>= 1.4), hgu133plus2.db, RCytoscape (>= 1.6), SPIA (>= 2.2), topologyGSA (>= 1.0), clipper, ALL License: AGPL-3 MD5sum: 51413869343320c7f42cfe73fc3b40ff NeedsCompilation: no Title: GRAPH Interaction from pathway Topological Environment Description: Graph objects from pathway topology derived from Biocarta, KEGG, NCI, Reactome and SPIKE databases. biocViews: Pathways, ConnectTools, GraphsAndNetworks Author: Gabriele Sales , Enrica Calura , Chiara Romualdi Maintainer: Gabriele Sales source.ver: src/contrib/graphite_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/graphite_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/graphite_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/graphite_1.6.0.tgz vignettes: vignettes/graphite/inst/doc/graphite.pdf vignetteTitles: GRAPH Interaction from pathway Topological Environment hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/graphite/inst/doc/graphite.R suggestsMe: clipper Package: GraphPAC Version: 1.2.2 Depends: R(>= 2.15),iPAC, igraph, TSP, RMallow Suggests: RUnit, BiocGenerics License: GPL-2 MD5sum: b1ab757ff42c85e9d77f67b4719ee52f NeedsCompilation: no Title: Identification of Mutational Clusters in Proteins via a Graph Theoretical Approach. Description: Identifies mutational clusters of amino acids in a protein while utilizing the proteins tertiary structure via a graph theoretical model. biocViews: Bioinformatics, Clustering, BiologicalDomains, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/GraphPAC_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/GraphPAC_1.2.2.zip win64.binary.ver: bin/windows64/contrib/2.16/GraphPAC_1.2.2.zip mac.binary.ver: bin/macosx/contrib/2.16/GraphPAC_1.2.2.tgz vignettes: vignettes/GraphPAC/inst/doc/GraphPAC.pdf vignetteTitles: iPAC: identification of Protein Amino acid Mutations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GraphPAC/inst/doc/GraphPAC.R Package: GRENITS Version: 1.12.0 Depends: R (>= 2.12.0), Rcpp (>= 0.8.6), RcppArmadillo (>= 0.2.8), ggplot2 (>= 0.9.0) Imports: graphics, grDevices, reshape2, stats, utils LinkingTo: Rcpp, RcppArmadillo Suggests: network License: GPL (>= 2) Archs: i386, x64 MD5sum: 58e4c62b9cbccb625e56a127a036aeee NeedsCompilation: yes Title: Gene Regulatory Network Inference Using Time Series Description: The package offers four network inference statistical models using Dynamic Bayesian Networks and Gibbs Variable Selection: a linear interaction model, two linear interaction models with added experimental noise (Gaussian and Student distributed) for the case where replicates are available and a non-linear interaction model. biocViews: NetworkInference, GeneRegulation, TimeCourse, GraphsAndNetworks Author: Edward Morrissey Maintainer: Edward Morrissey source.ver: src/contrib/GRENITS_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GRENITS_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GRENITS_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GRENITS_1.12.0.tgz vignettes: vignettes/GRENITS/inst/doc/GRENITS_package.pdf vignetteTitles: GRENITS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GRENITS/inst/doc/GRENITS_package.R Package: GSEABase Version: 1.22.0 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), annotate, methods, graph (>= 1.37.2) Imports: BiocGenerics, annotate, AnnotationDbi, Biobase, graph, methods, XML Suggests: hgu95av2.db, GO.db, org.Hs.eg.db, Rgraphviz, ReportingTools License: Artistic-2.0 MD5sum: 0808dc4b219b622630bc1f60e5f3ccca NeedsCompilation: no Title: Gene set enrichment data structures and methods Description: This package provides classes and methods to support Gene Set Enrichment Analysis (GSEA). biocViews: Infrastructure, Bioinformatics Author: Martin Morgan, Seth Falcon, Robert Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GSEABase_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GSEABase_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GSEABase_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GSEABase_1.22.0.tgz vignettes: vignettes/GSEABase/inst/doc/GSEABase.pdf vignetteTitles: An introduction to GSEABase hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSEABase/inst/doc/GSEABase.R dependsOnMe: AGDEX, BicARE, gCMAP, GSVA, PROMISE importsMe: Category, categoryCompare, cellHTS2, gCMAPWeb, GSRI, GSVA, HTSanalyzeR, PCpheno, phenoTest, PROMISE, ReportingTools suggestsMe: BiocCaseStudies, categoryCompare, gage, GlobalAncova, globaltest, GOstats, PGSEA, phenoTest Package: GSEAlm Version: 1.20.0 Depends: Biobase Suggests: GSEABase,Category, multtest, ALL, annotate, hgu95av2.db, genefilter, GOstats, RColorBrewer License: Artistic-2.0 MD5sum: a393a2fef023c116256a3c68abf857da NeedsCompilation: no Title: Linear Model Toolset for Gene Set Enrichment Analysis Description: Models and methods for fitting linear models to gene expression data, together with tools for computing and using various regression diagnostics. biocViews: Microarray, Bioinformatics Author: Assaf Oron, Robert Gentleman (with contributions from S. Falcon and Z. Jiang) Maintainer: Assaf Oron source.ver: src/contrib/GSEAlm_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GSEAlm_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GSEAlm_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GSEAlm_1.20.0.tgz vignettes: vignettes/GSEAlm/inst/doc/GSEAlm.pdf vignetteTitles: Linear models in GSEA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSEAlm/inst/doc/GSEAlm.R importsMe: gCMAP Package: GSRI Version: 2.8.0 Depends: R (>= 2.14.2), fdrtool Imports: methods, graphics, stats, utils, genefilter, Biobase, GSEABase, les (>= 1.1.6) Suggests: limma, hgu95av2.db Enhances: multicore License: GPL-3 MD5sum: 385325adb800a164cba9bc6690a324a7 NeedsCompilation: no Title: Gene Set Regulation Index Description: The GSRI package estimates the number of differentially expressed genes in gene sets, utilizing the concept of the Gene Set Regulation Index (GSRI). biocViews: Microarray, Transcription, DifferentialExpression, Genetics, Bioinformatics Author: Julian Gehring, Kilian Bartholome, Clemens Kreutz, Jens Timmer Maintainer: Julian Gehring URL: http://julian-gehring.github.com/GSRI/ source.ver: src/contrib/GSRI_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GSRI_2.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GSRI_2.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GSRI_2.8.0.tgz vignettes: vignettes/GSRI/inst/doc/gsri.pdf vignetteTitles: Introduction to the GSRI package: Estimating Regulatory Effects utilizing the Gene Set Regulation Index hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/GSRI/inst/doc/gsri.R Package: GSVA Version: 1.8.0 Depends: R (>= 2.13.0), methods, GSEABase (>= 1.17.4) Imports: methods, BiocGenerics, Biobase, GSEABase Suggests: limma, RColorBrewer, genefilter, mclust, edgeR, GSVAdata Enhances: snow, parallel License: GPL (>= 2) Archs: i386, x64 MD5sum: 259219a70968906dc5fa6564f6321468 NeedsCompilation: yes Title: Gene Set Variation Analysis for microarray and RNA-seq data Description: Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner. biocViews: Microarray, Pathways, GeneSetEnrichment Author: Justin Guinney (with contributions from Robert Castelo and Sonja Haenzelmann ) Maintainer: Justin Guinney URL: http://www.sagebase.org source.ver: src/contrib/GSVA_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/GSVA_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/GSVA_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/GSVA_1.8.0.tgz vignettes: vignettes/GSVA/inst/doc/GSVA.pdf vignetteTitles: Gene Set Variation Analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSVA/inst/doc/GSVA.R Package: Gviz Version: 1.4.5 Depends: R (>= 2.10.0), methods, grid Imports: IRanges (>= 1.13.19), rtracklayer (>= 1.15.5), lattice, RColorBrewer, biomaRt (>= 2.11.0), GenomicRanges (>= 1.7.14), AnnotationDbi (>= 1.17.11), Biobase (>= 2.15.3), BiocGenerics (>= 0.1.4), GenomicFeatures (>= 1.9.7), BSgenome (>= 1.25.1), Biostrings (>= 2.25.1), biovizBase (>= 1.5.7), Rsamtools(>= 1.11.1) Suggests: xtable, GenomicFeatures, BSgenome.Hsapiens.UCSC.hg19, biomaRt, rtracklayer License: Artistic-2.0 MD5sum: 7d174926d1313374fa13d9ac93859ae3 NeedsCompilation: no Title: Plotting data and annotation information along genomic coordinates Description: Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data. biocViews: Visualization, Microarray Author: Florian Hahne, Steffen Durinck, Robert Ivanek, Arne Mueller, Steve Lianoglou Maintainer: Florian Hahne source.ver: src/contrib/Gviz_1.4.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/Gviz_1.4.5.zip win64.binary.ver: bin/windows64/contrib/2.16/Gviz_1.4.5.zip mac.binary.ver: bin/macosx/contrib/2.16/Gviz_1.4.5.tgz vignettes: vignettes/Gviz/inst/doc/Gviz.pdf, vignettes/Gviz/inst/doc/ucsc1.pdf, vignettes/Gviz/inst/doc/ucsc2.pdf vignetteTitles: Gviz users guide, ucsc1.pdf, ucsc2.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Gviz/inst/doc/Gviz.R dependsOnMe: biomvRCNS, cummeRbund importsMe: methyAnalysis, PING suggestsMe: gwascat, QuasR, SplicingGraphs Package: gwascat Version: 1.4.0 Depends: R (>= 2.14.0), methods, IRanges, GenomicRanges, snpStats, graph, BiocGenerics Imports: Biostrings Suggests: DO.db, Gviz, ggbio, rtracklayer Enhances: SNPlocs.Hsapiens.dbSNP.20111119, pd.genomewidesnp.6 License: Artistic-2.0 MD5sum: 9b95d1148e6560690bcabdaf108a526e NeedsCompilation: no Title: representing and modeling data in the NHGRI GWAS catalog Description: representing and modeling data in the NHGRI GWAS catalog biocViews: genetics Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/gwascat_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/gwascat_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/gwascat_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/gwascat_1.4.0.tgz vignettes: vignettes/gwascat/inst/doc/gwascat.pdf vignetteTitles: gwascat -- exploring NHGRI GWAS catalog hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gwascat/inst/doc/gwascat.R Package: GWASTools Version: 1.6.5 Depends: Biobase, ncdf, gdsfmt, sandwich Imports: methods, DBI, RSQLite, GWASExactHW, DNAcopy, survival, lmtest, quantsmooth Suggests: GWASdata, BiocGenerics, RUnit, SNPRelate, snpStats, VariantAnnotation License: Artistic-2.0 MD5sum: e62b6aa4ae3c3e0b968feac6dc625be4 NeedsCompilation: no Title: Tools for Genome Wide Association Studies Description: Classes for storing very large GWAS data sets and annotation, and functions for GWAS data cleaning and analysis. biocViews: SNP, GeneticVariability, QualityControl, Microarray Author: Stephanie M. Gogarten, Cathy Laurie, Tushar Bhangale, Matthew P. Conomos, Cecelia Laurie, Caitlin McHugh, Ian Painter, Xiuwen Zheng, Jess Shen, Rohit Swarnkar Maintainer: Stephanie M. Gogarten source.ver: src/contrib/GWASTools_1.6.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/GWASTools_1.6.5.zip win64.binary.ver: bin/windows64/contrib/2.16/GWASTools_1.6.5.zip mac.binary.ver: bin/macosx/contrib/2.16/GWASTools_1.6.5.tgz vignettes: vignettes/GWASTools/inst/doc/Affymetrix.pdf, vignettes/GWASTools/inst/doc/DataCleaning.pdf, vignettes/GWASTools/inst/doc/Formats.pdf, vignettes/GWASTools/inst/doc/VCF.pdf vignetteTitles: Preparing Affymetrix Data, GWAS Data Cleaning, Data formats in GWASTools, Converting VCF data for use in GWASTools hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GWASTools/inst/doc/Affymetrix.R, vignettes/GWASTools/inst/doc/DataCleaning.R, vignettes/GWASTools/inst/doc/Formats.R, vignettes/GWASTools/inst/doc/VCF.R Package: hapFabia Version: 1.2.2 Depends: R (>= 2.12.0), Biobase, fabia (>= 2.3.1) Imports: methods, graphics, grDevices, stats, utils, KernSmooth License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: 4d110e7358183f52801885acda2ed6d2 NeedsCompilation: yes Title: hapFabia: Identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data Description: A package to identify very short IBD segments in large sequencing data by FABIA biclustering. Two haplotypes are identical by descent (IBD) if they share a segment that both inherited from a common ancestor. Current IBD methods reliably detect long IBD segments because many minor alleles in the segment are concordant between the two haplotypes. However, many cohort studies contain unrelated individuals which share only short IBD segments. This package provides software to identify short IBD segments in sequencing data. Knowledge of short IBD segments are relevant for phasing of genotyping data, association studies, and for population genetics, where they shed light on the evolutionary history of humans. The package supports VCF formats, is based on sparse matrix operations, and provides visualization of haplotype clusters in different formats. biocViews: Genetics, GeneticVariability, SNP, Sequencing, HighThroughputSequencing, Visualization, Clustering, SequenceMatching, Homo_sapiens, Software Author: Sepp Hochreiter Maintainer: Sepp Hochreiter URL: http://www.bioinf.jku.at/software/hapFabia/hapFabia.html source.ver: src/contrib/hapFabia_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/hapFabia_1.2.2.zip win64.binary.ver: bin/windows64/contrib/2.16/hapFabia_1.2.2.zip mac.binary.ver: bin/macosx/contrib/2.16/hapFabia_1.2.2.tgz vignettes: vignettes/hapFabia/inst/doc/hapfabia.pdf vignetteTitles: hapFabia: Manual for the R package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hapFabia/inst/doc/hapfabia.R Package: Harshlight Version: 1.32.1 Depends: R (>= 2.10) Imports: affy, altcdfenvs, Biobase, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 114a0f5619258046fb232504a6d19232 NeedsCompilation: yes Title: A "corrective make-up" program for microarray chips Description: The package is used to detect extended, diffuse and compact blemishes on microarray chips. Harshlight automatically marks the areas in a collection of chips (affybatch objects) and a corrected AffyBatch object is returned, in which the defected areas are substituted with NAs or the median of the values of the same probe in the other chips in the collection. The new version handle the substitute value as whole matrix to solve the memory problem. biocViews: Microarray, QualityControl, Preprocessing, AffymetrixChip, ReportWriting Author: Mayte Suarez-Farinas, Maurizio Pellegrino, Knut M. Wittkowski, Marcelo O. Magnasco Maintainer: Maurizio Pellegrino URL: http://asterion.rockefeller.edu/Harshlight/ source.ver: src/contrib/Harshlight_1.32.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/Harshlight_1.32.1.zip win64.binary.ver: bin/windows64/contrib/2.16/Harshlight_1.32.1.zip mac.binary.ver: bin/macosx/contrib/2.16/Harshlight_1.32.1.tgz vignettes: vignettes/Harshlight/inst/doc/Harshlight.pdf vignetteTitles: Harshlight hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Harshlight/inst/doc/Harshlight.R Package: HCsnip Version: 1.0.0 Depends: R(>= 2.10.0), survival, coin, fpc, clusterRepro, impute, randomForestSRC, sm, sigaR, Biobase License: GPL (>= 2) MD5sum: 66aa9fe57ca9e375a4ffaf55ed5033f6 NeedsCompilation: no Title: Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree Description: Decompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy. biocViews: Microarray, Bioinformatics, aCGH, GeneExpression, Clustering Author: Askar Obulkasim Maintainer: Askar Obulkasim source.ver: src/contrib/HCsnip_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HCsnip_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HCsnip_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HCsnip_1.0.0.tgz vignettes: vignettes/HCsnip/inst/doc/densityR.pdf, vignettes/HCsnip/inst/doc/entropy.pdf, vignettes/HCsnip/inst/doc/HCsnip.pdf, vignettes/HCsnip/inst/doc/Rank.pdf vignetteTitles: densityR.pdf, entropy.pdf, HCsnip, Rank.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HCsnip/inst/doc/HCsnip.R Package: Heatplus Version: 2.6.0 Imports: graphics, grDevices, stats Suggests: Biobase, hgu95av2.db, limma License: GPL (>= 2) MD5sum: 917e04a8043532e7c1858bd328c30c33 NeedsCompilation: no Title: Heatmaps with row and/or column covariates and colored clusters Description: Display a rectangular heatmap (intensity plot) of a data matrix. By default, both samples (columns) and features (row) of the matrix are sorted according to a hierarchical clustering, and the corresponding dendrogram is plotted. Optionally, panels with additional information about samples and features can be added to the plot. biocViews: Microarray, Visualization Author: Alexander Ploner Maintainer: Alexander Ploner source.ver: src/contrib/Heatplus_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Heatplus_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Heatplus_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Heatplus_2.6.0.tgz vignettes: vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.pdf, vignettes/Heatplus/inst/doc/annHeatmap.pdf, vignettes/Heatplus/inst/doc/oldHeatplus.pdf vignetteTitles: Commented package source, Annotated and regular heatmaps, Old functions (deprecated) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.R, vignettes/Heatplus/inst/doc/annHeatmap.R, vignettes/Heatplus/inst/doc/oldHeatplus.R dependsOnMe: GeneAnswers, phenoTest Package: HELP Version: 1.18.0 Depends: R (>= 2.8.0), stats, graphics, grDevices, Biobase, methods License: GPL (>= 2) MD5sum: ddc86bb62b0e38de1af054e25750d4b0 NeedsCompilation: no Title: Tools for HELP data analysis Description: The package contains a modular pipeline for analysis of HELP microarray data, and includes graphical and mathematical tools with more general applications biocViews: CpGIsland, DNAMethylation, Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, Visualization Author: Reid F. Thompson , John M. Greally , with contributions from Mark Reimers Maintainer: Reid F. Thompson source.ver: src/contrib/HELP_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HELP_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HELP_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HELP_1.18.0.tgz vignettes: vignettes/HELP/inst/doc/HELP.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HELP/inst/doc/HELP.R Package: HEM Version: 1.32.0 Depends: R (>= 2.1.0) Imports: Biobase, grDevices, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 138ce89e2b50234f157070964e37b209 NeedsCompilation: yes Title: Heterogeneous error model for identification of differentially expressed genes under multiple conditions Description: This package fits heterogeneous error models for analysis of microarray data biocViews: Microarray, DifferentialExpression, Bioinformatics Author: HyungJun Cho and Jae K. Lee Maintainer: HyungJun Cho URL: http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/ source.ver: src/contrib/HEM_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HEM_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HEM_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HEM_1.32.0.tgz vignettes: vignettes/HEM/inst/doc/HEM.pdf vignetteTitles: HEM Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HEM/inst/doc/HEM.R Package: HilbertVis Version: 1.18.0 Depends: R (>= 2.6.0), grid, lattice Suggests: IRanges, EBImage License: GPL (>= 3) Archs: i386, x64 MD5sum: ac765c63e2c8a98c2687cce6bd5e4883 NeedsCompilation: yes Title: Hilbert curve visualization Description: Functions to visualize long vectors of integer data by means of Hilbert curves biocViews: Visualization Author: Simon Anders Maintainer: Simon Anders URL: http://www.ebi.ac.uk/~anders/hilbert source.ver: src/contrib/HilbertVis_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HilbertVis_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HilbertVis_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HilbertVis_1.18.0.tgz vignettes: vignettes/HilbertVis/inst/doc/HilbertDisplay_GUI.pdf, vignettes/HilbertVis/inst/doc/HilbertVis.pdf, vignettes/HilbertVis/inst/doc/ThreeChTest.pdf vignetteTitles: HilbertDisplay_GUI.pdf, Visualising very long data vectors with the Hilbert curve, ThreeChTest.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HilbertVis/inst/doc/HilbertVis.R dependsOnMe: HilbertVisGUI importsMe: ChIPseqR Package: HilbertVisGUI Version: 1.18.0 Depends: R (>= 2.6.0), HilbertVis (>= 1.1.6) Suggests: lattice, IRanges License: GPL (>= 3) Archs: i386, x64 MD5sum: f8f73075eaee26314fcf946f3efbda70 NeedsCompilation: yes Title: HilbertVisGUI Description: An interactive tool to visualize long vectors of integer data by means of Hilbert curves biocViews: Visualization Author: Simon Anders Maintainer: Simon Anders URL: http://www.ebi.ac.uk/~anders/hilbert SystemRequirements: gtkmm-2.4 source.ver: src/contrib/HilbertVisGUI_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HilbertVisGUI_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HilbertVisGUI_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HilbertVisGUI_1.18.0.tgz vignettes: vignettes/HilbertVisGUI/inst/doc/HilbertVisGUI.pdf vignetteTitles: See vignette in package HilbertVis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: TRUE hasLICENSE: FALSE Rfiles: vignettes/HilbertVisGUI/inst/doc/HilbertVisGUI.R Package: HiTC Version: 1.4.0 Depends: R (>= 2.10.0), methods, GenomicRanges, IRanges, RColorBrewer Imports: methods, Biobase, Biostrings, graphics, grDevices, rtracklayer Suggests: rtracklayer License: Artistic-2.0 MD5sum: 325535ba74af66986a9e67f2a98ae700 NeedsCompilation: no Title: High Throughput Chromosome Conformation Capture analysis Description: The HiTC package was developed to explore high-throughput 'C' data such as 5C or Hi-C. biocViews: Sequencing, HighThroughputSequencing Author: Nicolas Servant Maintainer: Nicolas Servant source.ver: src/contrib/HiTC_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HiTC_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HiTC_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HiTC_1.4.0.tgz vignettes: vignettes/HiTC/inst/doc/HiTC.pdf vignetteTitles: Hight-Throughput Chromosome Conformation Capture analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HiTC/inst/doc/HiTC.R Package: HMMcopy Version: 1.2.0 Depends: R (>= 2.10.0), IRanges (>= 1.4.16), geneplotter (>= 1.24.0) License: GPL-3 Archs: i386, x64 MD5sum: 69a6ab5b90492632002eea228d63cf56 NeedsCompilation: yes Title: Copy number prediction with correction for GC and mappability bias for HTS data Description: Corrects GC and mappability biases for readcounts (i.e. coverage) in non-overlapping windows of fixed length for single whole genome samples, yielding a rough estimate of copy number for furthur analysis. Designed for rapid correction of high coverage whole genome tumour and normal samples. biocViews: Sequencing, Preprocessing, Visualization, CopyNumberVariants, HighThroughputSequencing, Microarray Author: Daniel Lai, Gavin Ha, Sohrab Shah Maintainer: Daniel Lai , Gavin Ha , Sohrab Shah source.ver: src/contrib/HMMcopy_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HMMcopy_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HMMcopy_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HMMcopy_1.2.0.tgz vignettes: vignettes/HMMcopy/inst/doc/HMMcopy.pdf vignetteTitles: HMMcopy hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HMMcopy/inst/doc/HMMcopy.R Package: hopach Version: 2.20.0 Depends: R (>= 2.11.0), cluster, Biobase, methods Imports: Biobase, cluster, graphics, grDevices, methods, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 9f4e0e65ed69d55e1404de44b8cddd76 NeedsCompilation: yes Title: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH) Description: The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering). biocViews: Clustering Author: Katherine S. Pollard, with Mark J. van der Laan and Greg Wall Maintainer: Katherine S. Pollard URL: http://www.stat.berkeley.edu/~laan/, http://docpollard.org/ source.ver: src/contrib/hopach_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/hopach_2.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/hopach_2.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/hopach_2.20.0.tgz vignettes: vignettes/hopach/inst/doc/bootplot.pdf, vignettes/hopach/inst/doc/dplot.pdf, vignettes/hopach/inst/doc/hopachManuscript.pdf, vignettes/hopach/inst/doc/hopach.pdf, vignettes/hopach/inst/doc/MSS.pdf vignetteTitles: bootplot.pdf, dplot.pdf, hopachManuscript.pdf, hopach, MSS.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hopach/inst/doc/hopach.R importsMe: phenoTest suggestsMe: BiocCaseStudies Package: hpar Version: 1.2.0 Depends: R (>= 2.15) Suggests: org.Hs.eg.db, GO.db, knitr License: Artistic-2.0 MD5sum: e0b8c8d722069cde6b52c734a4909d0a NeedsCompilation: no Title: Human Protein Atlas in R Description: A simple interface to and data from the Human Protein Atlas project. biocViews: Bioinformatics, Proteomics, Homo_sapiens, CellBiology Author: Laurent Gatto Maintainer: Laurent Gatto source.ver: src/contrib/hpar_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/hpar_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/hpar_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/hpar_1.2.0.tgz vignettes: vignettes/hpar/inst/doc/hpar.pdf vignetteTitles: hpar hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hpar/inst/doc/hpar.R Package: HTqPCR Version: 1.14.0 Depends: Biobase, RColorBrewer, limma Imports: affy, Biobase, gplots, graphics, grDevices, limma, methods, RColorBrewer, stats, stats4, utils Suggests: statmod License: Artistic-2.0 MD5sum: c6e54291e8aba9332146edbe6e1bc867 NeedsCompilation: no Title: Automated analysis of high-throughput qPCR data Description: Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. The input data can be from spatially-defined formats such ABI TaqMan Low Density Arrays or OpenArray; LightCycler from Roche Applied Science; the CFX plates from Bio-Rad Laboratories; conventional 96- or 384-well plates; or microfluidic devices such as the Dynamic Arrays from Fluidigm Corporation. HTqPCR handles data loading, quality assessment, normalization, visualization and parametric or non-parametric testing for statistical significance in Ct values between features (e.g. genes, microRNAs). biocViews: MicrotitrePlateAssay, DifferentialExpression, GeneExpression, DataImport, QualityControl, Preprocessing, Bioinformatics, Visualization, MultipleComparisons, qPCR Author: Heidi Dvinge, Paul Bertone Maintainer: Heidi Dvinge URL: http://www.ebi.ac.uk/bertone/software source.ver: src/contrib/HTqPCR_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HTqPCR_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HTqPCR_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HTqPCR_1.14.0.tgz vignettes: vignettes/HTqPCR/inst/doc/HTqPCR.pdf vignetteTitles: qPCR analysis in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTqPCR/inst/doc/HTqPCR.R Package: HTSanalyzeR Version: 2.12.1 Depends: R (>= 2.15), igraph0, methods Imports: graph, igraph0, GSEABase, BioNet, cellHTS2, AnnotationDbi, biomaRt, RankProd Suggests: KEGG.db, GO.db, org.Dm.eg.db, GOstats, org.Ce.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Hs.eg.db, snow License: Artistic-2.0 MD5sum: 17728b3d8d14cbd77656c71620bafa65 NeedsCompilation: no Title: Gene set over-representation, enrichment and network analyses for high-throughput screens Description: This package provides classes and methods for gene set over-representation, enrichment and network analyses on high-throughput screens. The over-representation analysis is performed based on hypergeometric tests. The enrichment analysis is based on the GSEA algorithm (Subramanian et al. PNAS 2005). The network analysis identifies enriched subnetworks based on algorithms from the BioNet package (Beisser et al., Bioinformatics 2010). A pipeline is also specifically designed for cellHTS2 object to perform integrative network analyses of high-throughput RNA interference screens. The users can build their own analysis pipeline for their own data set based on this package. biocViews: CellBasedAssays, Bioinformatics, MultipleComparisons Author: Xin Wang , Camille Terfve , John C. Rose , Florian Markowetz Maintainer: Xin Wang source.ver: src/contrib/HTSanalyzeR_2.12.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/HTSanalyzeR_2.12.1.zip win64.binary.ver: bin/windows64/contrib/2.16/HTSanalyzeR_2.12.1.zip mac.binary.ver: bin/macosx/contrib/2.16/HTSanalyzeR_2.12.1.tgz vignettes: vignettes/HTSanalyzeR/inst/doc/Figure.pdf, vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.pdf vignetteTitles: Figure.pdf, Main vignette:Gene set enrichment and network analysis of high-throughput RNAi screen data using HTSanalyzeR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.R importsMe: phenoTest Package: HTSeqGenie Version: 3.10.0 Depends: R (>= 2.15.0), ShortRead (>= 1.14.4), parallel, hwriter, Cairo, tools, rtracklayer, gmapR (>= 1.1.10) Imports: BiocGenerics (>= 0.2.0), IRanges (>= 1.14.3), GenomicRanges (>= 1.7.12), Rsamtools (>= 1.8.5), Biostrings (>= 2.24.1), chipseq (>= 1.6.1), rtracklayer (>= 1.17.19), GenomicFeatures (>= 1.9.31), VariantTools (>= 1.1.16), VariantAnnotation (>= 1.5.41) Suggests: TxDb.Hsapiens.UCSC.hg19.knownGene, GenomicFeatures, LungCancerLines, org.Hs.eg.db License: Artistic-2.0 MD5sum: ff55a5097e56f8431497d8f8d298fd64 NeedsCompilation: no Title: A NGS analysis pipeline. Description: Libraries to perform NGS analysis. Author: Gregoire Pau, Jens Reeder Maintainer: Gregoire Pau source.ver: src/contrib/HTSeqGenie_3.10.0.tar.gz vignettes: vignettes/HTSeqGenie/inst/doc/HTSeqGenie.pdf vignetteTitles: gmapR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTSeqGenie/inst/doc/HTSeqGenie.R Package: htSeqTools Version: 1.6.1 Depends: R (>= 2.12.2), methods, BiocGenerics (>= 0.1.0), Biobase, IRanges, methods, MASS, BSgenome, GenomicRanges Enhances: parallel License: GPL (>=2) MD5sum: b4e58e5d15c422c50aadae34631c17dd NeedsCompilation: no Title: Quality Control, Visualization and Processing for High-Throughput Sequencing data Description: We provide efficient, easy-to-use tools for High-Throughput Sequencing (ChIP-seq, RNAseq etc.). These include MDS plots (analogues to PCA), detecting inefficient immuno-precipitation or over-amplification artifacts, tools to identify and test for genomic regions with large accumulation of reads, and visualization of coverage profiles. biocViews: HighThroughputSequencing,QualityControl Author: Evarist Planet, Camille Stephan-Otto, Oscar Reina, Oscar Flores, David Rossell Maintainer: Oscar Reina source.ver: src/contrib/htSeqTools_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/htSeqTools_1.6.1.zip win64.binary.ver: bin/windows64/contrib/2.16/htSeqTools_1.6.1.zip mac.binary.ver: bin/macosx/contrib/2.16/htSeqTools_1.6.1.tgz vignettes: vignettes/htSeqTools/inst/doc/htSeqTools.pdf vignetteTitles: Manual for the htSeqTools library hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/htSeqTools/inst/doc/htSeqTools.R Package: HTSFilter Version: 1.0.1 Depends: methods, Biobase (>= 2.16.0), R (>= 2.10.0) Imports: DESeq (>= 1.8.3), edgeR (>= 2.6.12), DESeq2, GenomicRanges, IRanges Suggests: EDASeq (>= 1.2.0) License: Artistic-2.0 MD5sum: 70647d7afef80be436b4a1d504106372 NeedsCompilation: no Title: Filter replicated high-throughput transcriptome sequencing data Description: This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions. biocViews: HighThroughputSequencing, RNAseq, Preprocessing, DifferentialExpression Author: Andrea Rau, Melina Gallopin, Gilles Celeux, and Florence Jaffrezic Maintainer: Andrea Rau source.ver: src/contrib/HTSFilter_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/HTSFilter_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/HTSFilter_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/HTSFilter_1.0.1.tgz vignettes: vignettes/HTSFilter/inst/doc/HTSFilter.pdf vignetteTitles: HTSFilter Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTSFilter/inst/doc/HTSFilter.R Package: HybridMTest Version: 1.4.0 Depends: R (>= 2.9.0), Biobase, fdrtool, MASS, survival Imports: stats License: GPL Version 2 or later MD5sum: d8310aae98334e0e08124e3bd69c62c1 NeedsCompilation: no Title: Hybrid Multiple Testing Description: Performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using empirical Bayes probability (EBP) estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weigth. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs. biocViews: GeneExpression, Genetics, Bioinformatics, Microarray Author: Stan Pounds , Demba Fofana Maintainer: Demba Fofana source.ver: src/contrib/HybridMTest_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/HybridMTest_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/HybridMTest_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/HybridMTest_1.4.0.tgz vignettes: vignettes/HybridMTest/inst/doc/HybridMTest.pdf vignetteTitles: Hybrid Multiple Testing hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HybridMTest/inst/doc/HybridMTest.R Package: hyperdraw Version: 1.12.0 Depends: R (>= 2.9.0), methods, grid, graph, hypergraph, Rgraphviz Imports: stats4 License: GPL (>= 2) MD5sum: 49ef97dfb5e59d656ef887d7d29aff10 NeedsCompilation: no Title: Visualizing Hypergaphs Description: Functions for visualizing hypergraphs. biocViews: NetworkVisualization, GraphsAndNetworks Author: Paul Murrell Maintainer: Paul Murrell SystemRequirements: graphviz source.ver: src/contrib/hyperdraw_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/hyperdraw_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/hyperdraw_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/hyperdraw_1.12.0.tgz vignettes: vignettes/hyperdraw/inst/doc/hyperdraw.pdf vignetteTitles: Hyperdraw hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hyperdraw/inst/doc/hyperdraw.R Package: hypergraph Version: 1.32.0 Depends: R (>= 2.1.0), methods, graph License: Artistic-2.0 MD5sum: f27563b930ad05461ccaceca02a51af7 NeedsCompilation: no Title: A package providing hypergraph data structures Description: A package that implements some simple capabilities for representing and manipulating hypergraphs. biocViews: GraphsAndNetworks Author: Seth Falcon, Robert Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/hypergraph_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/hypergraph_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/hypergraph_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/hypergraph_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: altcdfenvs, hyperdraw, RpsiXML Package: iASeq Version: 1.4.0 Depends: R (>= 2.14.1) Imports: graphics, grDevices License: GPL-2 MD5sum: f4e7d7aff87d4146cd0f43860c838efb NeedsCompilation: no Title: iASeq: integrating multiple sequencing datasets for detecting allele-specific events Description: It fits correlation motif model to multiple RNAseq or ChIPseq studies to improve detection of allele-specific events and describe correlation patterns across studies. biocViews: SNP, RNAseq, ChIPseq, Bioinformatics Author: Yingying Wei, Hongkai Ji Maintainer: Yingying Wei source.ver: src/contrib/iASeq_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iASeq_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iASeq_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iASeq_1.4.0.tgz vignettes: vignettes/iASeq/inst/doc/iASeqVignette.pdf vignetteTitles: iASeq Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iASeq/inst/doc/iASeqVignette.R Package: iBBiG Version: 1.4.0 Depends: biclust Imports: stats4,xtable,ade4 Suggests: methods License: Artistic-2.0 Archs: i386, x64 MD5sum: cdb06eba3bfffd5f66cbe1ed9b4d48e9 NeedsCompilation: yes Title: Iterative Binary Biclustering of Genesets Description: iBBiG is a bi-clustering algorithm which is optimizes for binary data analysis. We apply it to meta-gene set analysis of large numbers of gene expression datasets. The iterative algorithm extracts groups of phenotypes from multiple studies that are associated with similar gene sets. iBBiG does not require prior knowledge of the number or scale of clusters and allows discovery of clusters with diverse sizes biocViews: Clustering, Annotation, GeneSetEnrichment Author: Daniel Gusenleitner, Aedin Culhane Maintainer: Aedin Culhane URL: http://bcb.dfci.harvard.edu/~aedin/publications/ source.ver: src/contrib/iBBiG_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iBBiG_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iBBiG_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iBBiG_1.4.0.tgz vignettes: vignettes/iBBiG/inst/doc/tutorial.pdf vignetteTitles: iBBiG User Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iBBiG/inst/doc/tutorial.R Package: ibh Version: 1.8.0 Depends: simpIntLists Suggests: yeastCC, stats License: GPL (>= 2) MD5sum: a7ef3642f1c0168661e5f91a9936095b NeedsCompilation: no Title: Interaction Based Homogeneity for Evaluating Gene Lists Description: This package contains methods for calculating Interaction Based Homogeneity to evaluate fitness of gene lists to an interaction network which is useful for evaluation of clustering results and gene list analysis. BioGRID interactions are used in the calculation. The user can also provide their own interactions. biocViews: QualityControl, DataImport, GraphsAndNetworks, NetworkEnrichment Author: Kircicegi Korkmaz, Volkan Atalay, Rengul Cetin Atalay. Maintainer: Kircicegi Korkmaz source.ver: src/contrib/ibh_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ibh_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ibh_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ibh_1.8.0.tgz vignettes: vignettes/ibh/inst/doc/ibh.pdf vignetteTitles: ibh hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ibh/inst/doc/ibh.R Package: iBMQ Version: 1.0.1 Depends: R(>= 2.15.0),Biobase (>= 2.16.0), ggplot2 (>= 0.9.2) License: Artistic-2.0 OS_type: unix MD5sum: 419194561adee67bd71521854c6f71c2 NeedsCompilation: yes Title: integrated Bayesian Modeling of eQTL data Description: integrated Bayesian Modeling of eQTL data biocViews: Microarray, Preprocessing, GeneExpression, SNP Author: Marie-Pier Scott-Boyer and Greg Imholte Maintainer: Marie-Pier Scott-Boyer URL: http://www.rglab.org SystemRequirements: GSL and OpenMP source.ver: src/contrib/iBMQ_1.0.1.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/iBMQ_1.0.1.tgz vignettes: vignettes/iBMQ/inst/doc/iBMQ.pdf vignetteTitles: iBMQ: An Integrated Hierarchical Bayesian Model for Multivariate eQTL Mapping hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iBMQ/inst/doc/iBMQ.R Package: Icens Version: 1.32.0 Depends: survival Imports: graphics License: Artistic-2.0 MD5sum: 462f92c915a8bf2620317d120526570e NeedsCompilation: no Title: NPMLE for Censored and Truncated Data Description: Many functions for computing the NPMLE for censored and truncated data. biocViews: Bioinformatics, Infrastructure Author: R. Gentleman and Alain Vandal Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Icens_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Icens_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Icens_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Icens_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: PROcess importsMe: PROcess Package: iChip Version: 1.14.0 Depends: R (>= 2.10.0) Imports: limma License: GPL (>= 2) Archs: i386, x64 MD5sum: e846157b164318047e68f5229a737bbb NeedsCompilation: yes Title: Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models Description: This package uses hidden Ising models to identify enriched genomic regions in ChIP-chip data. It can be used to analyze the data from multiple platforms (e.g., Affymetrix, Agilent, and NimbleGen), and the data with single to multiple replicates. biocViews: ChIPchip, NimbleGen, Affymetrix, Agilent,Microarray, Bioinformatics Author: Qianxing Mo Maintainer: Qianxing Mo source.ver: src/contrib/iChip_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iChip_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iChip_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iChip_1.14.0.tgz vignettes: vignettes/iChip/inst/doc/iChip.pdf vignetteTitles: iChip hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iChip/inst/doc/iChip.R Package: idiogram Version: 1.36.0 Depends: R (>= 2.10), methods, Biobase, annotate, plotrix Suggests: hu6800.db, hgu95av2.db, golubEsets License: GPL-2 MD5sum: 57759e1dd99a629aaabf951b5c3e343e NeedsCompilation: no Title: idiogram Description: A package for plotting genomic data by chromosomal location biocViews: Visualization Author: Karl J. Dykema Maintainer: Karl J. Dykema source.ver: src/contrib/idiogram_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/idiogram_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/idiogram_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/idiogram_1.36.0.tgz vignettes: vignettes/idiogram/inst/doc/idiogram.pdf vignetteTitles: HOWTO: idiogram hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/idiogram/inst/doc/idiogram.R dependsOnMe: reb Package: IdMappingAnalysis Version: 1.4.0 Depends: R (>= 2.14), R.oo (>= 1.10.1), rChoiceDialogs Imports: boot, mclust, RColorBrewer, Biobase License: GPL-2 MD5sum: ca0c457ab282d3886f1f1b744a38647f NeedsCompilation: no Title: ID Mapping Analysis Description: Identifier mapping performance analysis biocViews: Bioinformatics, Annotation, MultipleComparisons Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/IdMappingAnalysis_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/IdMappingAnalysis_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/IdMappingAnalysis_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/IdMappingAnalysis_1.4.0.tgz vignettes: vignettes/IdMappingAnalysis/inst/doc/IdMappingAnalysis.pdf vignetteTitles: Critically comparing identifier maps retrieved from bioinformatics annotation resources. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IdMappingAnalysis/inst/doc/IdMappingAnalysis.R Package: IdMappingRetrieval Version: 1.6.0 Depends: R.oo, XML, RCurl, rChoiceDialogs, ENVISIONQuery Imports: biomaRt, ENVISIONQuery, DAVIDQuery, AffyCompatible, R.methodsS3, R.oo, utils License: GPL-2 MD5sum: 1f88956c95d7ca7146821235e19586ce NeedsCompilation: no Title: ID Mapping Data Retrieval Description: Data retrieval for identifier mapping performance analysis biocViews: Bioinformatics, Annotation, MultipleComparisons Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/IdMappingRetrieval_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/IdMappingRetrieval_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/IdMappingRetrieval_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/IdMappingRetrieval_1.6.0.tgz vignettes: vignettes/IdMappingRetrieval/inst/doc/IdMappingRetrieval.pdf vignetteTitles: Collection and subsequent fast retrieval of identifier mapping related information from various online sources. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IdMappingRetrieval/inst/doc/IdMappingRetrieval.R Package: iFlow Version: 2.12.0 Depends: R (>= 2.13.0), flowCore, flowViz, flowStats (>= 1.3.20) Imports: Biobase, RGtk2, cairoDevice, flowCore, flowStats, flowViz, grDevices, graphics, methods, utils License: Artistic-2.0 MD5sum: 372de5df186fa46d8f6640158fb9de6b NeedsCompilation: no Title: GUI based visualization for flow cytometry Description: Tool to explore and visualize flow cytometry biocViews: FlowCytometry, Bioinformatics, GUI Author: Kyongryun Lee, Florian Hahne, Deepayan Sarkar Maintainer: Kyongryun Lee URL: http://www.hindawi.com/journals/abi/2009/103839.html source.ver: src/contrib/iFlow_2.12.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/iFlow_2.12.0.tgz vignettes: vignettes/iFlow/inst/doc/iflow.pdf vignetteTitles: How to iFlow hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iFlow/inst/doc/iflow.R Package: illuminaio Version: 0.2.0 Suggests: RUnit, BiocGenerics, minfiData, hapmap370k License: Artistic-2.0 MD5sum: e1a3d82928a39fd16e76afb6d249126a NeedsCompilation: no Title: Parsing Illumina microarray output files Description: Tools for parsing Illumina's microarray output files, including IDAT. biocViews: Infrastructure, DataImport Author: Keith Baggerly, Henrik Bengtsson, Kasper Daniel Hansen, Matt Ritchie Maintainer: Kasper Daniel Hansen source.ver: src/contrib/illuminaio_0.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/illuminaio_0.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/illuminaio_0.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/illuminaio_0.2.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE importsMe: crlmm, minfi Package: imageHTS Version: 1.10.0 Depends: R (>= 2.9.0), EBImage (>= 4.1.6), cellHTS2 (>= 2.10.0) Imports: tools, Biobase, hwriter, methods, vsn, stats, utils, e1071 Suggests: MASS License: LGPL-2.1 MD5sum: 06b0ed2970f238bebda7e2e8405927f8 NeedsCompilation: no Title: Analysis of high-throughput microscopy-based screens Description: imageHTS is an R package dedicated to the analysis of high-throughput microscopy-based screens. The package provides a modular and extensible framework to segment cells, extract quantitative cell features, predict cell types and browse screen data through web interfaces. Designed to operate in distributed environments, imageHTS provides a standardized access to remote data and facilitates the dissemination of high-throughput microscopy-based datasets. biocViews: CellBasedAssays, Visualization, Preprocessing Author: Gregoire Pau, Xian Zhang, Michael Boutros, Wolfgang Huber Maintainer: Gregoire Pau source.ver: src/contrib/imageHTS_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/imageHTS_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/imageHTS_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/imageHTS_1.10.0.tgz vignettes: vignettes/imageHTS/inst/doc/imageHTS-introduction.pdf vignetteTitles: Analysis of high-throughput microscopy-based screens with imageHTS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/imageHTS/inst/doc/imageHTS-introduction.R dependsOnMe: phenoDist Package: impute Version: 1.34.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: e003306568955eab148161b3e2ebbf59 NeedsCompilation: yes Title: impute: Imputation for microarray data Description: Imputation for microarray data (currently KNN only) biocViews: Bioinformatics, Microarray Author: Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu Maintainer: Balasubramanian Narasimhan source.ver: src/contrib/impute_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/impute_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/impute_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/impute_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: HCsnip importsMe: MSnbase suggestsMe: BioNet Package: inSilicoDb Version: 1.8.0 Depends: R (>= 2.11.0), rjson, Biobase Imports: RCurl Suggests: limma License: GPL-2 MD5sum: 06b31de270f7bd44b21550db98f5ee37 NeedsCompilation: no Title: Access to the InSilico Database Description: Access Human Affymetrix expert curated Gene Expression Omnibus (GEO) datasets from the InSilico Database. biocViews: Microarray, DataImport Author: Jonatan Taminau Maintainer: Jonatan Taminau , David Steenhoff URL: https://insilicodb.org source.ver: src/contrib/inSilicoDb_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/inSilicoDb_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/inSilicoDb_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/inSilicoDb_1.8.0.tgz vignettes: vignettes/inSilicoDb/inst/doc/inSilicoDb.pdf vignetteTitles: Using the inSilicoDb package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inSilicoDb/inst/doc/inSilicoDb.R suggestsMe: inSilicoMerging Package: inSilicoMerging Version: 1.4.1 Depends: R (>= 2.11.1), Biobase, DWD Suggests: BiocGenerics, inSilicoDb License: GPL-2 MD5sum: df6faf3f105e1819bf985047ca1e4769 NeedsCompilation: no Title: Collection of Merging Techniques for Gene Expression Data Description: Collection of techniques to remove inter-study bias when combining gene expression data originating from different studies. biocViews: Microarray Author: Jonatan Taminau Maintainer: Jonatan Taminau , Stijn Meganck URL: http://insilico.ulb.ac.be/insilico-project/ source.ver: src/contrib/inSilicoMerging_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/inSilicoMerging_1.4.1.zip win64.binary.ver: bin/windows64/contrib/2.16/inSilicoMerging_1.4.1.zip mac.binary.ver: bin/macosx/contrib/2.16/inSilicoMerging_1.4.1.tgz vignettes: vignettes/inSilicoMerging/inst/doc/inSilicoMerging.pdf vignetteTitles: Using the inSilicoMerging package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inSilicoMerging/inst/doc/inSilicoMerging.R Package: inveRsion Version: 1.8.0 Depends: methods, haplo.stats Imports: graphics, methods, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 8a321e3fd2f211087669da68f2f72191 NeedsCompilation: yes Title: Inversions in genotype data Description: Package to find genetic inversions in genotype (SNP array) data. biocViews: Microarray, SNP Author: Alejandro Caceres Maintainer: Alejandro Caceres source.ver: src/contrib/inveRsion_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/inveRsion_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/inveRsion_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/inveRsion_1.8.0.tgz vignettes: vignettes/inveRsion/inst/doc/inveRsion.pdf, vignettes/inveRsion/inst/doc/Manual.pdf vignetteTitles: Quick start guide for inveRsion package, Manual.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inveRsion/inst/doc/inveRsion.R Package: iontree Version: 1.6.0 Depends: methods, rJava, RSQLite, XML Suggests: iontreeData License: GPL-2 MD5sum: 108af31cbcc75c394c0182a8c513cdcf NeedsCompilation: no Title: Data management and analysis of ion trees from ion-trap mass spectrometry Description: Ion fragmentation provides structural information for metabolite identification. This package provides utility functions to manage and analyse MS2/MS3 fragmentation data from ion trap mass spectrometry. It was designed for high throughput metabolomics data with many biological samples and a large numer of ion trees collected. Tests have been done with data from low-resolution mass spectrometry but could be readily extended to precursor ion based fragmentation data from high resoultion mass spectrometry. biocViews: Metabolomics, MassSpectrometry Author: Mingshu Cao Maintainer: Mingshu Cao source.ver: src/contrib/iontree_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iontree_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iontree_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iontree_1.6.0.tgz vignettes: vignettes/iontree/inst/doc/iontree_doc.pdf vignetteTitles: MSn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/iontree/inst/doc/iontree_doc.R Package: iPAC Version: 1.4.2 Depends: R(>= 2.15),gdata, scatterplot3d, Biostrings, multtest License: GPL-2 MD5sum: 509f35cabbceaf0a9387fdc0e205ada8 NeedsCompilation: no Title: Identification of Protein Amino acid Clustering Description: iPAC is a novel tool to identify somatic amino acid mutation clustering within proteins while taking into account protein structure. biocViews: Bioinformatics, Clustering, BiologicalDomains, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/iPAC_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/iPAC_1.4.2.zip win64.binary.ver: bin/windows64/contrib/2.16/iPAC_1.4.2.zip mac.binary.ver: bin/macosx/contrib/2.16/iPAC_1.4.2.tgz vignettes: vignettes/iPAC/inst/doc/iPAC.pdf vignetteTitles: iPAC: identification of Protein Amino acid Mutations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iPAC/inst/doc/iPAC.R Package: IPPD Version: 1.8.0 Depends: R (>= 2.12.0), MASS, Matrix, XML, digest, bitops Imports: methods, stats, graphics License: GPL (version 2 or later) Archs: i386, x64 MD5sum: aaebe0fdc4c4c8120d8d409a193bd924 NeedsCompilation: yes Title: Isotopic peak pattern deconvolution for Protein Mass Spectrometry by template matching Description: The package provides functionality to extract isotopic peak patterns from raw mass spectra. This is done by fitting a large set of template basis functions to the raw spectrum using either nonnegative least squares or least absolute deviation fittting. The package offers a flexible function which tries to estimate model parameters in a way tailored to the peak shapes in the data. The package also provides functionality to process LCMS runs. biocViews: Proteomics Author: Martin Slawski , Rene Hussong , Matthias Hein Maintainer: Martin Slawski source.ver: src/contrib/IPPD_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/IPPD_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/IPPD_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/IPPD_1.8.0.tgz vignettes: vignettes/IPPD/inst/doc/IPPD.pdf, vignettes/IPPD/inst/doc/templatedetail.pdf, vignettes/IPPD/inst/doc/templates.pdf vignetteTitles: IPPD Manual, templatedetail.pdf, templates.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IPPD/inst/doc/IPPD.R Package: IRanges Version: 1.18.4 Depends: R (>= 2.8.0), methods, utils, stats, BiocGenerics (>= 0.5.6) Imports: methods, utils, stats, BiocGenerics, stats4 Suggests: GenomicRanges, RUnit, BSgenome.Celegans.UCSC.ce2 License: Artistic-2.0 Archs: i386, x64 MD5sum: 6b227190f72cb6d082fb11229095b67f NeedsCompilation: yes Title: Infrastructure for manipulating intervals on sequences Description: The package provides efficient low-level and highly reusable S4 classes for storing ranges of integers, RLE vectors (Run-Length Encoding), and, more generally, data that can be organized sequentially (formally defined as Vector objects), as well as views on these Vector objects. Efficient list-like classes are also provided for storing big collections of instances of the basic classes. All classes in the package use consistent naming and share the same rich and consistent "Vector API" as much as possible. biocViews: Infrastructure, DataRepresentation Author: H. Pages, P. Aboyoun and M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/IRanges_1.18.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/IRanges_1.18.4.zip win64.binary.ver: bin/windows64/contrib/2.16/IRanges_1.18.4.zip mac.binary.ver: bin/macosx/contrib/2.16/IRanges_1.18.4.tgz vignettes: vignettes/IRanges/inst/doc/IRangesOverview.pdf, vignettes/IRanges/inst/doc/RleTricks.pdf vignetteTitles: An Introduction to IRanges, Rle Tips and Tricks hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IRanges/inst/doc/IRangesOverview.R, vignettes/IRanges/inst/doc/RleTricks.R dependsOnMe: AnnotationHub, BayesPeak, biomvRCNS, Biostrings, BiSeq, BSgenome, bsseq, bumphunter, casper, ChIPpeakAnno, chipseq, chroGPS, cn.mops, CSAR, DASiR, DECIPHER, deepSNV, DESeq2, DirichletMultinomial, easyRNASeq, epigenomix, exomeCopy, genomes, GenomicFeatures, GenomicRanges, Genominator, genoset, GGtools, girafe, gwascat, HiTC, HMMcopy, htSeqTools, methyAnalysis, MinimumDistance, MotifDb, nucleR, oneChannelGUI, PING, rGADEM, RIPSeeker, rMAT, Rsamtools, segmentSeq, ShortRead, SomatiCA, SplicingGraphs, TEQC, triform, VariantAnnotation, VariantTools, xmapcore importsMe: annmap, AnnotationDbi, ArrayExpressHTS, BayesPeak, Biostrings, biovizBase, BiSeq, BitSeq, CAGEr, charm, ChIPpeakAnno, chipseq, ChIPseqR, ChIPsim, ChromHeatMap, cn.mops, copynumber, DECIPHER, DESeq2, DiffBind, EDASeq, ensemblVEP, epigenomix, fastseg, flowQ, FunciSNP, gCMAPWeb, gcrma, GenomicFeatures, GenomicRanges, ggbio, girafe, gmapR, Gviz, HTSeqGenie, HTSFilter, MEDIPS, methVisual, methyAnalysis, MethylSeekR, mosaics, motifRG, MotIV, MSnbase, NarrowPeaks, nucleR, oligoClasses, OTUbase, pdInfoBuilder, PICS, prebs, QuasR, R453Plus1Toolbox, Rcade, REDseq, Repitools, rGADEM, rMAT, rnaSeqMap, Rolexa, Rsamtools, rSFFreader, RSVSim, rtracklayer, segmentSeq, ShortRead, SomatiCA, SplicingGraphs, triform, TSSi, VanillaICE, VariantAnnotation, VariantTools, waveTiling suggestsMe: BiocGenerics, HilbertVis, HilbertVisGUI, MiRaGE, Repitools, SNPchip Package: iSeq Version: 1.12.0 Depends: R (>= 2.10.0) License: GPL (>= 2) Archs: i386, x64 MD5sum: 819fbac4a3e5eb0a79fd66e51b6eb9f8 NeedsCompilation: yes Title: Bayesian Hierarchical Modeling of ChIP-seq Data Through Hidden Ising Models Description: This package uses Bayesian hidden Ising models to identify IP-enriched genomic regions from ChIP-seq data. It can be used to analyze ChIP-seq data with and without controls and replicates. biocViews: ChIPseq, HighThroughputSequencing, Bioinformatics Author: Qianxing Mo Maintainer: Qianxing Mo source.ver: src/contrib/iSeq_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iSeq_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iSeq_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iSeq_1.12.0.tgz vignettes: vignettes/iSeq/inst/doc/iSeq.pdf vignetteTitles: iSeq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iSeq/inst/doc/iSeq.R Package: isobar Version: 1.6.6 Depends: R (>= 2.10.0), Biobase, stats, methods, plyr Imports: distr Suggests: MSnbase, OrgMassSpecR, XML, biomaRt, ggplot2, RJSONIO, Hmisc, gplots, RColorBrewer, gridExtra, limma, boot, distr License: LGPL-2 MD5sum: e1226086211c76456a5e9b22f555bbc9 NeedsCompilation: no Title: Analysis and quantitation of isobarically tagged MSMS proteomics data Description: isobar provides methods for preprocessing, normalization, and report generation for the analysis of quantitative mass spectrometry proteomics data labeled with isobaric tags, such as iTRAQ and TMT. biocViews: Proteomics, MassSpectrometry, Bioinformatics, MultipleComparisons, QualityControl Author: Florian P Breitwieser and Jacques Colinge , with contributions from Xavier Robin and Florent Gluck Maintainer: Florian P Breitwieser URL: http://bioinformatics.cemm.oeaw.ac.at source.ver: src/contrib/isobar_1.6.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/isobar_1.6.6.zip win64.binary.ver: bin/windows64/contrib/2.16/isobar_1.6.6.zip mac.binary.ver: bin/macosx/contrib/2.16/isobar_1.6.6.tgz vignettes: vignettes/isobar/inst/doc/isobar-devel.pdf, vignettes/isobar/inst/doc/isobar.pdf, vignettes/isobar/inst/doc/isobar-ptm.pdf vignetteTitles: isobar for developers, isobar package for iTRAQ and TMT protein quantification, isobar for quantification of PTM datasets hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/isobar/inst/doc/isobar-devel.R, vignettes/isobar/inst/doc/isobar-ptm.R, vignettes/isobar/inst/doc/isobar.R Package: IsoGeneGUI Version: 1.16.0 Depends: tcltk, tkrplot, IsoGene Imports: multtest, relimp, WriteXLS,gdata, RColorBrewer, geneplotter Suggests: RUnit License: GPL-2 MD5sum: 58bb7e5b69fa023de96e11033eb3dfca NeedsCompilation: no Title: A graphical user interface to conduct a dose-response analysis of microarray data Description: The IsoGene Graphical User Interface (IsoGene-GUI) is a user friendly interface of the IsoGene package which is aimed to identify for genes with a monotonic trend in the expression levels with respect to the increasing doses using several test statistics: global likelihood ratio test (E2), Bartholomew 1961, Barlow et al. 1972 and Robertson et al. 1988), Williams (1971, 1972), Marcus (1976), the M (Hu et al. 2005) and the modified M (Lin et al. 2007). The p-values of the global likelihood ratio test (E2) are obtained using the excat distribution and permutation. The other four test statistics are obtained using permutation . Several p-values adjustment are provided: Bonferroni, Holm (1979), Hochberg (1988), and Sidak procedures for controlling the family-wise Type I error rate (FWER), and BH (Benjamini and Hochberg 1995) and BY (Benjamini and Yekutieli 2001) procedures are used for controlling the FDR. the inference is based on resampling methods, which control the False Discovery Rate (FDR) (both permutations (Ge et al., 2003) and the Significance Analysis of Microarrays (SAM), Tusher et al., 2001). biocViews: Microarray, DifferentialExpression, GUI Author: Setia Pramana, Dan Lin, Philippe Haldermans, Tobias Verbeke Maintainer: Setia Pramana URL: http://www.ibiostat.be/software/IsoGeneGUI/index.html source.ver: src/contrib/IsoGeneGUI_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/IsoGeneGUI_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/IsoGeneGUI_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/IsoGeneGUI_1.16.0.tgz vignettes: vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.pdf vignetteTitles: IsoGeneGUI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.R Package: ITALICS Version: 2.20.0 Depends: R (>= 2.0.0), GLAD, ITALICSData, oligo, affxparser, pd.mapping50k.xba240 Imports: affxparser, DBI, GLAD, oligo, oligoClasses, stats Suggests: pd.mapping50k.hind240, pd.mapping250k.sty, pd.mapping250k.nsp License: GPL-2 MD5sum: 651d882aa5098023deb692ee3f83926e NeedsCompilation: no Title: ITALICS Description: A Method to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set biocViews: Microarray, CopyNumberVariants Author: Guillem Rigaill, Philippe Hupe Maintainer: Guillem Rigaill URL: http://bioinfo.curie.fr source.ver: src/contrib/ITALICS_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ITALICS_2.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ITALICS_2.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ITALICS_2.20.0.tgz vignettes: vignettes/ITALICS/inst/doc/ITALICS-006.pdf, vignettes/ITALICS/inst/doc/ITALICS.pdf vignetteTitles: ITALICS-006.pdf, ITALICS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ITALICS/inst/doc/ITALICS.R Package: iterativeBMA Version: 1.18.0 Depends: BMA, leaps, Biobase (>= 2.5.5) License: GPL (>= 2) MD5sum: 1cc1ef858e6d6ff42f9eeb47d3f00c61 NeedsCompilation: no Title: The Iterative Bayesian Model Averaging (BMA) algorithm Description: The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402). biocViews: Microarray, Bioinformatics, Classification Author: Ka Yee Yeung, University of Washington, Seattle, WA, with contributions from Adrian Raftery and Ian Painter Maintainer: Ka Yee Yeung URL: http://faculty.washington.edu/kayee/research.html source.ver: src/contrib/iterativeBMA_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iterativeBMA_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iterativeBMA_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iterativeBMA_1.18.0.tgz vignettes: vignettes/iterativeBMA/inst/doc/iterativeBMA.pdf vignetteTitles: The Iterative Bayesian Model Averaging Algorithm hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iterativeBMA/inst/doc/iterativeBMA.R Package: iterativeBMAsurv Version: 1.18.0 Depends: BMA, leaps, survival, splines Imports: graphics, grDevices, stats, survival, utils License: GPL (>= 2) MD5sum: 7bc9ecc20b06233265f076ad6525246f NeedsCompilation: no Title: The Iterative Bayesian Model Averaging (BMA) Algorithm For Survival Analysis Description: The iterative Bayesian Model Averaging (BMA) algorithm for survival analysis is a variable selection method for applying survival analysis to microarray data. biocViews: Microarray, Bioinformatics Author: Amalia Annest, University of Washington, Tacoma, WA Ka Yee Yeung, University of Washington, Seattle, WA Maintainer: Ka Yee Yeung URL: http://expression.washington.edu/ibmasurv/protected source.ver: src/contrib/iterativeBMAsurv_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/iterativeBMAsurv_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/iterativeBMAsurv_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/iterativeBMAsurv_1.18.0.tgz vignettes: vignettes/iterativeBMAsurv/inst/doc/iterativeBMAsurv.pdf vignetteTitles: The Iterative Bayesian Model Averaging Algorithm For Survival Analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iterativeBMAsurv/inst/doc/iterativeBMAsurv.R Package: jmosaics Version: 1.0.0 Depends: R (>= 2.15.2), mosaics License: GPL (>= 2) MD5sum: ad574a51b2bb4ff360668b01b7367401 NeedsCompilation: no Title: Joint analysis of multiple ChIP-Seq data sets Description: jmosaics detects enriched regions of ChIP-seq data sets jointly. biocViews: ChIPseq, Sequencing, Transcription, Genetics, Bioinformatics Author: Xin Zeng Maintainer: Xin Zeng source.ver: src/contrib/jmosaics_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/jmosaics_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/jmosaics_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/jmosaics_1.0.0.tgz vignettes: vignettes/jmosaics/inst/doc/jmosaics-h3k27me3_g1e-plot.pdf, vignettes/jmosaics/inst/doc/jmosaics-h3k4me1_g1e-plot.pdf, vignettes/jmosaics/inst/doc/jmosaics.pdf vignetteTitles: jmosaics-h3k27me3_g1e-plot.pdf, jmosaics-h3k4me1_g1e-plot.pdf, jMOSAiCS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/jmosaics/inst/doc/jmosaics.R Package: joda Version: 1.8.0 Depends: R (>= 2.0), bgmm, RBGL License: GPL (>= 2) MD5sum: 7f2e1e628b7ed3d56a56ab5c9be963e4 NeedsCompilation: no Title: JODA algorithm for quantifying gene deregulation using knowledge Description: Package 'joda' implements three steps of an algorithm called JODA. The algorithm computes gene deregulation scores. For each gene, its deregulation score reflects how strongly an effect of a certain regulator's perturbation on this gene differs between two different cell populations. The algorithm utilizes regulator knockdown expression data as well as knowledge about signaling pathways in which the regulators are involved (formalized in a simple matrix model). biocViews: Microarray, Pathways, GraphsAndNetworks, Statistics, NetworkInference Author: Ewa Szczurek Maintainer: Ewa Szczurek URL: http://www.bioconductor.org source.ver: src/contrib/joda_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/joda_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/joda_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/joda_1.8.0.tgz vignettes: vignettes/joda/inst/doc/JodaVignette.pdf vignetteTitles: Introduction to joda hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/joda/inst/doc/JodaVignette.R Package: KCsmart Version: 2.18.0 Depends: siggenes, multtest, KernSmooth Imports: methods, BiocGenerics Enhances: Biobase, CGHbase License: GPL-3 MD5sum: 65c1aed1e4ab0296edc9e1895fea448a NeedsCompilation: no Title: Multi sample aCGH analysis package using kernel convolution Description: Multi sample aCGH analysis package using kernel convolution biocViews: CopyNumberVariants, Visualization, aCGH, Microarray Author: Jorma de Ronde, Christiaan Klijn, Arno Velds Maintainer: Jorma de Ronde source.ver: src/contrib/KCsmart_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/KCsmart_2.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/KCsmart_2.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/KCsmart_2.18.0.tgz vignettes: vignettes/KCsmart/inst/doc/KCS.pdf vignetteTitles: KCsmart example session hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KCsmart/inst/doc/KCS.R Package: KEGGgraph Version: 1.16.0 Depends: R (>= 2.10), methods, XML (>= 2.3-0), graph Imports: methods, XML, graph Suggests: Rgraphviz, RBGL, RUnit, RColorBrewer, KEGG.db, org.Hs.eg.db, hgu133plus2.db, SPIA License: GPL (>= 2) MD5sum: dea991303b632e02e6cc39d417278518 NeedsCompilation: no Title: KEGGgraph: A graph approach to KEGG PATHWAY in R and Bioconductor Description: KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essential pathway attributes. The package offers functionalities including parsing, graph operation, visualization and etc. biocViews: Pathways, GraphsAndNetworks, NetworkVisualization Author: Jitao David Zhang Maintainer: Jitao David Zhang URL: http://www.nextbiomotif.com source.ver: src/contrib/KEGGgraph_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/KEGGgraph_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/KEGGgraph_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/KEGGgraph_1.16.0.tgz vignettes: vignettes/KEGGgraph/inst/doc/KEGGgraphApp.pdf, vignettes/KEGGgraph/inst/doc/KEGGgraph.pdf vignetteTitles: KEGGgraph: Application Examples, KEGGgraph: graph approach to KEGG PATHWAY hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGgraph/inst/doc/KEGGgraphApp.R, vignettes/KEGGgraph/inst/doc/KEGGgraph.R dependsOnMe: pathview, ROntoTools, SPIA importsMe: clipper, DEGraph, NCIgraph suggestsMe: DEGraph Package: keggorthology Version: 2.12.0 Depends: R (>= 2.5.0),stats,graph,hgu95av2.db Imports: AnnotationDbi,graph,DBI, graph, grDevices, methods, stats, tools, utils Suggests: RBGL,ALL License: Artistic-2.0 MD5sum: 47ffe1926e765cd3a4077d8eb81858c0 NeedsCompilation: no Title: graph support for KO, KEGG Orthology Description: graphical representation of the Feb 2010 KEGG Orthology. The KEGG orthology is a set of pathway IDs that are not to be confused with the KEGG ortholog IDs. biocViews: Pathways, GraphsAndNetworks, NetworkVisualization Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/keggorthology_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/keggorthology_2.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/keggorthology_2.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/keggorthology_2.12.0.tgz vignettes: vignettes/keggorthology/inst/doc/keggorth.pdf vignetteTitles: keggorthology overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/keggorthology/inst/doc/keggorth.R suggestsMe: MLInterfaces Package: KEGGprofile Version: 1.2.0 Depends: XML, png, TeachingDemos, KEGG.db Imports: AnnotationDbi License: GPL (>= 2) MD5sum: 5988e27e046d31934d43cb90d9a00d69 NeedsCompilation: no Title: An annotation and visualization package for multi-types and multi-groups expression data in KEGG pathway Description: KEGGprofile is an annotation and visualization tool which integrated the expression profiles and the function annotation in KEGG pathway maps. The multi-types and multi-groups expression data can be visualized in one pathway map. KEGGprofile facilitated more detailed analysis about the specific function changes inner pathway or temporal correlations in different genes and samples. biocViews: Pathways Author: Shilin Zhao Maintainer: Shilin Zhao source.ver: src/contrib/KEGGprofile_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/KEGGprofile_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/KEGGprofile_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/KEGGprofile_1.2.0.tgz vignettes: vignettes/KEGGprofile/inst/doc/KEGGprofile.pdf vignetteTitles: KEGGprofile: Application Examples hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGprofile/inst/doc/KEGGprofile.R Package: KEGGREST Version: 1.0.1 Imports: methods, httr, png, Biostrings Suggests: RUnit, BiocGenerics, knitr License: Artistic-2.0 MD5sum: d8b8371f2dde34b7bee027b3d3094abe NeedsCompilation: no Title: Client-side REST access to KEGG Description: A package that provides a client interface to the KEGG REST server. Based on KEGGSOAP by J. Zhang, R. Gentleman, and Marc Carlson, and KEGG (python package) by Aurelien Mazurie. biocViews: Annotation, Pathways, ConnectTools Author: Dan Tenenbaum Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/KEGGREST_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/KEGGREST_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/KEGGREST_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/KEGGREST_1.0.1.tgz vignettes: vignettes/KEGGREST/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGREST/inst/doc/KEGGREST-vignette.R htmlDocs: vignettes/KEGGREST/inst/doc/KEGGREST-vignette.html htmlTitles: "Accessing the KEGG REST API" dependsOnMe: PAPi, ROntoTools Package: KEGGSOAP Version: 1.34.0 Depends: methods, BiocGenerics Imports: XML, RCurl, SSOAP (>= 0.2-2), XMLSchema Suggests: RUnit License: BSD MD5sum: 67f9399ad5412b5b9f0b1a1f6336f086 NeedsCompilation: no Title: Client-side SOAP access KEGG Description: A package that provides a client interface to the KEGG SOAP server biocViews: Annotation, Pathways, ConnectTools Author: J. Zhang and R. Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/KEGGSOAP_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/KEGGSOAP_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/KEGGSOAP_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/KEGGSOAP_1.34.0.tgz hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: lapmix Version: 1.26.0 Depends: R (>= 2.6.0),stats Imports: Biobase, graphics, grDevices, methods, stats, tools, utils License: GPL (>= 2) MD5sum: 532278bd04b1da180300b0f02282ef42 NeedsCompilation: no Title: Laplace Mixture Model in Microarray Experiments Description: Laplace mixture modelling of microarray experiments. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes. The main purpose is to identify differentially expressed genes. biocViews: Bioinformatics, Microarray, OneChannel, DifferentialExpression Author: Yann Ruffieux, contributions from Debjani Bhowmick, Anthony C. Davison, and Darlene R. Goldstein Maintainer: Yann Ruffieux URL: http://www.r-project.org, http://www.bioconductor.org, http://stat.epfl.ch source.ver: src/contrib/lapmix_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/lapmix_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/lapmix_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/lapmix_1.26.0.tgz vignettes: vignettes/lapmix/inst/doc/lapmix-example.pdf vignetteTitles: lapmix example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lapmix/inst/doc/lapmix-example.R Package: LBE Version: 1.28.0 Depends: stats Imports: graphics, grDevices, methods, stats, utils Suggests: qvalue License: GPL-2 MD5sum: 763025be63a9f63720dd49ee5df5eb9d NeedsCompilation: no Title: Estimation of the false discovery rate. Description: LBE is an efficient procedure for estimating the proportion of true null hypotheses, the false discovery rate (and so the q-values) in the framework of estimating procedures based on the marginal distribution of the p-values without assumption for the alternative hypothesis. biocViews: Bioinformatics, MultipleComparisons Author: Cyril Dalmasso Maintainer: Cyril Dalmasso source.ver: src/contrib/LBE_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/LBE_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/LBE_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/LBE_1.28.0.tgz vignettes: vignettes/LBE/inst/doc/LBE.pdf vignetteTitles: LBE Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LBE/inst/doc/LBE.R Package: les Version: 1.10.0 Depends: R (>= 2.13.2), methods, graphics, fdrtool Imports: boot, gplots, RColorBrewer Suggests: Biobase, limma Enhances: multicore License: GPL-3 MD5sum: 0ec2881e29b85360adfd7ff4a218974b NeedsCompilation: no Title: Identifying Differential Effects in Tiling Microarray Data Description: The 'les' package estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes. biocViews: Microarray, Bioinformatics, DifferentialExpression, ChIPchip, DNAMethylation, Transcription Author: Julian Gehring, Clemens Kreutz, Jens Timmer Maintainer: Julian Gehring URL: http://julian-gehring.github.com/les/ source.ver: src/contrib/les_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/les_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/les_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/les_1.10.0.tgz vignettes: vignettes/les/inst/doc/les.pdf vignetteTitles: Introduction to the les package: Identifying Differential Effects in Tiling Microarray Data with the Loci of Enhanced Significance Framework hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/les/inst/doc/les.R importsMe: GSRI Package: limma Version: 3.16.8 Depends: R (>= 2.3.0), methods Suggests: affy, MASS, org.Hs.eg.db, splines, statmod (>= 1.2.2), vsn, ellipse License: GPL (>=2) Archs: i386, x64 MD5sum: c7234e7c4f7149a22c0118a474556bd1 NeedsCompilation: yes Title: Linear Models for Microarray Data Description: Data analysis, linear models and differential expression for microarray data. biocViews: Microarray, OneChannel, TwoChannel, DataImport, QualityControl, Preprocessing, Bioinformatics, DifferentialExpression, MultipleComparisons, TimeCourse Author: Gordon Smyth with contributions from Matthew Ritchie, Jeremy Silver, James Wettenhall, Natalie Thorne, Mette Langaas, Egil Ferkingstad, Marcus Davy, Francois Pepin, Dongseok Choi, Davis McCarthy, Di Wu, Alicia Oshlack, Carolyn de Graaf, Yifang Hu, Wei Shi and Belinda Phipson. Maintainer: Gordon Smyth URL: http://bioinf.wehi.edu.au/limma source.ver: src/contrib/limma_3.16.8.tar.gz win.binary.ver: bin/windows/contrib/2.16/limma_3.16.8.zip win64.binary.ver: bin/windows64/contrib/2.16/limma_3.16.8.zip mac.binary.ver: bin/macosx/contrib/2.16/limma_3.16.8.tgz vignettes: vignettes/limma/inst/doc/limma.pdf, vignettes/limma/inst/doc/usersguide.pdf vignetteTitles: Limma Vignette, usersguide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/limma/inst/doc/limma.R dependsOnMe: a4Base, AffyExpress, affylmGUI, Agi4x44PreProcess, attract, birta, CALIB, cghMCR, ChIPpeakAnno, codelink, convert, Cormotif, coRNAi, DrugVsDisease, edgeR, ExiMiR, gCMAP, HTqPCR, limmaGUI, lmdme, maDB, maigesPack, marray, metagenomeSeq, MmPalateMiRNA, nem, PADOG, qpcrNorm, Ringo, snapCGH, SSPA, TurboNorm, wateRmelon importsMe: affycoretools, ArrayExpress, arrayQuality, arrayQualityMetrics, ArrayTools, attract, beadarray, betr, bumphunter, CALIB, CancerMutationAnalysis, charm, ChIPpeakAnno, explorase, GeneSelectMMD, GeneSelector, GGBase, HTqPCR, iChip, maSigPro, minfi, MmPalateMiRNA, OLIN, PADOG, phenoTest, Ringo, RNAinteract, RNAither, RTopper, snapCGH, timecourse, tweeDEseq, vsn suggestsMe: ABarray, beadarraySNP, BiocCaseStudies, BioNet, bumphunter, Category, categoryCompare, CMA, coGPS, dyebias, GeneSelector, GEOquery, GSRI, GSVA, Heatplus, inSilicoDb, isobar, les, lumi, methylumi, MLP, oligo, oneChannelGUI, PGSEA, piano, plw, PREDA, puma, Rcade, RTopper, rtracklayer, virtualArray Package: limmaGUI Version: 1.36.0 Depends: limma, tcltk Suggests: statmod, R2HTML, xtable, tkrplot License: LGPL MD5sum: 745bce84d07d3eef05f606897cf21fc6 NeedsCompilation: no Title: GUI for limma package Description: A Graphical User Interface for the limma Microarray package biocViews: Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, Bioinformatics, DifferentialExpression, MultipleComparisons, GUI Author: James Wettenhall Division of Genetics and Bioinformatics, WEHI Maintainer: Keith Satterley URL: http://bioinf.wehi.edu.au/limmaGUI/ source.ver: src/contrib/limmaGUI_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/limmaGUI_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/limmaGUI_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/limmaGUI_1.36.0.tgz vignettes: vignettes/limmaGUI/inst/doc/extract.pdf, vignettes/limmaGUI/inst/doc/limmaGUI.pdf, vignettes/limmaGUI/inst/doc/LinModIntro.pdf vignetteTitles: Extracting limma objects from limmaGUI files, limmaGUI Vignette, LinModIntro.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/limmaGUI/inst/doc/extract.R, vignettes/limmaGUI/inst/doc/limmaGUI.R htmlDocs: vignettes/limmaGUI/inst/doc/about.html, vignettes/limmaGUI/inst/doc/CustMenu.html, vignettes/limmaGUI/inst/doc/import.html, vignettes/limmaGUI/inst/doc/index.html, vignettes/limmaGUI/inst/doc/InputFiles.html, vignettes/limmaGUI/inst/doc/lgDevel.html, vignettes/limmaGUI/inst/doc/windowsFocus.html htmlTitles: "About limmaGUI", "Customizing the menus in limmaGUI (for Advanced users)", "Importing MA Data into LimmaGUI", "limmaGUI Documentation", "InputFiles.html", "LimmaGUI Developers' Guide", "Troubleshooting Window Focus Problems" Package: LiquidAssociation Version: 1.14.0 Depends: geepack, methods, yeastCC, org.Sc.sgd.db Imports: Biobase, graphics, grDevices, methods, stats License: GPL (>=3) MD5sum: 1b9bf6a5759ba4991ba3499f4fc3e4f6 NeedsCompilation: no Title: LiquidAssociation Description: The package contains functions for calculate direct and model-based estimators for liquid association. It also provides functions for testing the existence of liquid association given a gene triplet data. biocViews: Pathways, GeneExpression, CellBiology, Genetics, NetworkAnalysis, TimeCourse Author: Yen-Yi Ho Maintainer: Yen-Yi Ho source.ver: src/contrib/LiquidAssociation_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/LiquidAssociation_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/LiquidAssociation_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/LiquidAssociation_1.14.0.tgz vignettes: vignettes/LiquidAssociation/inst/doc/LiquidAssociation.pdf vignetteTitles: LiquidAssociation Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LiquidAssociation/inst/doc/LiquidAssociation.R Package: lmdme Version: 1.2.1 Depends: R (>= 2.14.1), methods, limma, pls, stemHypoxia Imports: stats Enhances: parallel License: GPL (>=2) MD5sum: 5fb8733ab29bdd0fcace2b95fc8d0569 NeedsCompilation: no Title: Linear Model decomposition for Designed Multivariate Experiments Description: linear ANOVA decomposition of Multivariate Designed Experiments implementation based on limma lmFit. Features: i)Flexible formula type interface, ii) Fast limma based implementation, iii) p-values for each estimated coefficient levels in each factor, iv) F values for factor effects and v) plotting functions for PCA and PLS. biocViews: Microarray, OneChannel, TwoChannel, Bioinformatics, Visualization, AssayDomains, DifferentialExpression, ExperimentData, Cancer Author: Cristobal Fresno and Elmer A. Fernandez Maintainer: Cristobal Fresno URL: http://www.bdmg.com.ar/?page_id=38 source.ver: src/contrib/lmdme_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/lmdme_1.2.1.zip win64.binary.ver: bin/windows64/contrib/2.16/lmdme_1.2.1.zip mac.binary.ver: bin/macosx/contrib/2.16/lmdme_1.2.1.tgz vignettes: vignettes/lmdme/inst/doc/lmdme-vignette.pdf vignetteTitles: lmdme: Linear Model on Designed Multivariate Experiments in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lmdme/inst/doc/lmdme-vignette.R Package: LMGene Version: 2.16.0 Depends: R (>= 2.10.0), Biobase (>= 2.5.5), multtest, survival, affy Suggests: affydata License: LGPL MD5sum: c5c6b5af8856d0577092abc31cece0dd NeedsCompilation: no Title: LMGene Software for Data Transformation and Identification of Differentially Expressed Genes in Gene Expression Arrays Description: LMGene package for analysis of microarray data using a linear model and glog data transformation biocViews: Microarray, Bioinformatics, DifferentialExpression, Preprocessing Author: David Rocke, Geun Cheol Lee, John Tillinghast, Blythe Durbin-Johnson, and Shiquan Wu Maintainer: Blythe Durbin-Johnson URL: http://dmrocke.ucdavis.edu/software.html source.ver: src/contrib/LMGene_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/LMGene_2.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/LMGene_2.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/LMGene_2.16.0.tgz vignettes: vignettes/LMGene/inst/doc/LMGene.pdf vignetteTitles: LMGene User's Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LMGene/inst/doc/LMGene.R Package: logicFS Version: 1.30.0 Depends: LogicReg, mcbiopi Suggests: genefilter, siggenes License: LGPL (>= 2) MD5sum: f8fd77263c9cfbc15cc2a8fcd2913d93 NeedsCompilation: no Title: Identification of SNP Interactions Description: Identification of interactions between binary variables using Logic Regression. Can, e.g., be used to find interesting SNP interactions. Contains also a bagging version of logic regression for classification. biocViews: SNP, Classification, Genetics Author: Holger Schwender Maintainer: Holger Schwender source.ver: src/contrib/logicFS_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/logicFS_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/logicFS_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/logicFS_1.30.0.tgz vignettes: vignettes/logicFS/inst/doc/logicFS.pdf vignetteTitles: logicFS Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/logicFS/inst/doc/logicFS.R Package: logitT Version: 1.18.0 Depends: affy Suggests: SpikeInSubset License: GPL (>= 2) Archs: i386, x64 MD5sum: 532c043f11ff7eaf2fa597a739b53f9b NeedsCompilation: yes Title: logit-t Package Description: The logitT library implements the Logit-t algorithm introduced in --A high performance test of differential gene expression for oligonucleotide arrays-- by William J Lemon, Sandya Liyanarachchi and Ming You for use with Affymetrix data stored in an AffyBatch object in R. biocViews: Microarray, DifferentialExpression Author: Tobias Guennel Maintainer: Tobias Guennel URL: http://www.bioconductor.org source.ver: src/contrib/logitT_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/logitT_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/logitT_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/logitT_1.18.0.tgz vignettes: vignettes/logitT/inst/doc/logitT.pdf vignetteTitles: logitT primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/logitT/inst/doc/logitT.R Package: lol Version: 1.8.0 Depends: penalized, Matrix Imports: Matrix, penalized, graphics, grDevices, stats License: GPL-2 MD5sum: a56cd8e1727cc73e265e1228f18a8af3 NeedsCompilation: no Title: Lots Of Lasso Description: Various optimization methods for Lasso inference with matrix warpper Author: Yinyin Yuan Maintainer: Yinyin Yuan source.ver: src/contrib/lol_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/lol_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/lol_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/lol_1.8.0.tgz vignettes: vignettes/lol/inst/doc/lol.pdf vignetteTitles: An introduction to the lol package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lol/inst/doc/lol.R Package: LPE Version: 1.34.0 Depends: R (>= 2.10) Imports: stats License: LGPL MD5sum: 0b36a4b596feaa861c3384f42c0c5405 NeedsCompilation: no Title: Methods for analyzing microarray data using Local Pooled Error (LPE) method Description: This LPE library is used to do significance analysis of microarray data with small number of replicates. It uses resampling based FDR adjustment, and gives less conservative results than traditional 'BH' or 'BY' procedures. Data accepted is raw data in txt format from MAS4, MAS5 or dChip. Data can also be supplied after normalization. LPE library is primarily used for analyzing data between two conditions. To use it for paired data, see LPEP library. For using LPE in multiple conditions, use HEM library. biocViews: Microarray, Bioinformatics, DifferentialExpression Author: Nitin Jain , Michael O'Connell , Jae K. Lee . Includes R source code contributed by HyungJun Cho Maintainer: Nitin Jain URL: http://www.r-project.org, http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/, http://sourceforge.net/projects/r-lpe/ source.ver: src/contrib/LPE_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/LPE_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/LPE_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/LPE_1.34.0.tgz vignettes: vignettes/LPE/inst/doc/LPE.pdf vignetteTitles: LPE test for microarray data with small number of replicates hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LPE/inst/doc/LPE.R dependsOnMe: LPEadj, PLPE importsMe: LPEadj suggestsMe: ABarray Package: LPEadj Version: 1.20.0 Depends: LPE Imports: LPE, stats License: LGPL MD5sum: a05c4568cc0a28581b548dd7e0165ab4 NeedsCompilation: no Title: A correction of the local pooled error (LPE) method to replace the asymptotic variance adjustment with an unbiased adjustment based on sample size. Description: Two options are added to the LPE algorithm. The original LPE method sets all variances below the max variance in the ordered distribution of variances to the maximum variance. in LPEadj this option is turned off by default. The second option is to use a variance adjustment based on sample size rather than pi/2. By default the LPEadj uses the sample size based variance adjustment. biocViews: Microarray, Bioinformatics, Proteomics Author: Carl Murie , Robert Nadon Maintainer: Carl Murie source.ver: src/contrib/LPEadj_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/LPEadj_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/LPEadj_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/LPEadj_1.20.0.tgz vignettes: vignettes/LPEadj/inst/doc/LPEadj.pdf vignetteTitles: LPEadj test for microarray data with small number of replicates hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LPEadj/inst/doc/LPEadj.R Package: lpNet Version: 1.0.0 Depends: lpSolve, nem License: Artistic License 2.0 MD5sum: 0b5b44701178f964e8817ed83bfc0fed NeedsCompilation: no Title: Linear Programming Model for Network Inference Description: lpNet takes perturbation data as input and generates an LP model which allows the inference of signaling networks. For parameter identification either leave-one-out cross-validation or stratified n-fold cross-validation can be used. Author: Bettina Knapp, Johanna Mazur, Lars Kaderali Maintainer: Bettina Knapp source.ver: src/contrib/lpNet_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/lpNet_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/lpNet_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/lpNet_1.0.0.tgz vignettes: vignettes/lpNet/inst/doc/vignette_lpNet.pdf vignetteTitles: lpNet,, network inference with a linear optimization program. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lpNet/inst/doc/vignette_lpNet.R Package: lumi Version: 2.12.0 Depends: R (>= 2.10), Biobase (>= 2.5.5) Imports: affy (>= 1.23.4), methylumi (>= 2.3.2), annotate, Biobase (>= 2.5.5), lattice, mgcv (>= 1.4-0), hdrcde, nleqslv, KernSmooth, preprocessCore, RSQLite, DBI, AnnotationDbi, MASS, graphics, stats, stats4, methods Suggests: beadarray, limma, vsn, lumiBarnes, lumiHumanAll.db, lumiHumanIDMapping, genefilter, RColorBrewer License: LGPL (>= 2) MD5sum: 4ef6e653a2af3b53d0640591f1abb51d NeedsCompilation: no Title: BeadArray Specific Methods for Illumina Methylation and Expression Microarrays Description: The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays. biocViews: Microarray, OneChannel, Preprocessing, DNAMethylation, QualityControl, TwoChannel Author: Pan Du, Richard Bourgon, Gang Feng, Simon Lin Maintainer: Pan Du source.ver: src/contrib/lumi_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/lumi_2.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/lumi_2.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/lumi_2.12.0.tgz vignettes: vignettes/lumi/inst/doc/Bioc2007_lumi_presentation.pdf, vignettes/lumi/inst/doc/IlluminaAnnotation.pdf, vignettes/lumi/inst/doc/lumi.pdf, vignettes/lumi/inst/doc/lumi_VST_evaluation.pdf, vignettes/lumi/inst/doc/methylationAnalysis.pdf vignetteTitles: Bioc2007_lumi_presentation.pdf, Resolve the inconsistency of Illumina identifiers through nuID, Using lumi A package processing Illumina Microarray, Evaluation of VST algorithm in lumi package, Analyze Illumina Infinium methylation microarray data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lumi/inst/doc/IlluminaAnnotation.R, vignettes/lumi/inst/doc/lumi.R, vignettes/lumi/inst/doc/lumi_VST_evaluation.R, vignettes/lumi/inst/doc/methylationAnalysis.R dependsOnMe: arrayMvout, wateRmelon importsMe: ffpe, methyAnalysis, MineICA suggestsMe: beadarray, methylumi, tigre, virtualArray Package: LVSmiRNA Version: 1.10.0 Depends: R (>= 2.10), Biobase,quantreg,splines,MASS,limma,affy,methods, SparseM, vsn Imports: BiocGenerics, stats4 Enhances: parallel,snow, Rmpi License: GPL-2 Archs: i386, x64 MD5sum: 5e0b10a0ffbce69fc1f2816782d36e20 NeedsCompilation: yes Title: LVS normalization for Agilent miRNA data Description: Normalization of Agilent miRNA arrays. biocViews: Microarray,AgilentChip,OneChannel,Preprocessing Author: Stefano Calza, Suo Chen, Yudi Pawitan Maintainer: Stefano Calza source.ver: src/contrib/LVSmiRNA_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/LVSmiRNA_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/LVSmiRNA_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/LVSmiRNA_1.10.0.tgz vignettes: vignettes/LVSmiRNA/inst/doc/LVSmiRNA.pdf vignetteTitles: LVSmiRNA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LVSmiRNA/inst/doc/LVSmiRNA.R Package: maanova Version: 1.30.0 Depends: R (>= 2.10) Imports: Biobase, graphics, grDevices, methods, stats, utils Suggests: qvalue, snow Enhances: Rmpi License: GPL (>= 2) Archs: i386, x64 MD5sum: 2f40d7336a6294176e7042935c2a257a NeedsCompilation: yes Title: Tools for analyzing Micro Array experiments Description: Analysis of N-dye Micro Array experiment using mixed model effect. Containing analysis of variance, permutation and bootstrap, cluster and consensus tree. biocViews: Microarray, DifferentialExpression, Clustering Author: Hao Wu, modified by Hyuna Yang and Keith Sheppard with ideas from Gary Churchill, Katie Kerr and Xiangqin Cui. Maintainer: Keith Sheppard URL: http://research.jax.org/faculty/churchill source.ver: src/contrib/maanova_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/maanova_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/maanova_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/maanova_1.30.0.tgz vignettes: vignettes/maanova/inst/doc/abf1fig.pdf, vignettes/maanova/inst/doc/hckidney.pdf, vignettes/maanova/inst/doc/maanova.pdf, vignettes/maanova/inst/doc/vgprofile.pdf vignetteTitles: abf1fig.pdf, hckidney.pdf, R/maanova HowTo, vgprofile.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maanova/inst/doc/maanova.R Package: macat Version: 1.34.0 Depends: Biobase, annotate Suggests: hgu95av2.db, stjudem License: Artistic-2.0 MD5sum: 41ba46d4828d8590787bd736b1173cb0 NeedsCompilation: no Title: MicroArray Chromosome Analysis Tool Description: This library contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. MACAT is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions. The functions have been tested on a publicly available data set about acute lymphoblastic leukemia (Yeoh et al.Cancer Cell 2002), which is provided in the library 'stjudem'. biocViews: Microarray, DifferentialExpression, Visualization Author: Benjamin Georgi, Matthias Heinig, Stefan Roepcke, Sebastian Schmeier, Joern Toedling Maintainer: Joern Toedling source.ver: src/contrib/macat_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/macat_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/macat_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/macat_1.34.0.tgz vignettes: vignettes/macat/inst/doc/chrom6TkNN.pdf, vignettes/macat/inst/doc/chrom6T.pdf, vignettes/macat/inst/doc/evalkNN6.pdf, vignettes/macat/inst/doc/macat.pdf, vignettes/macat/inst/doc/Slidingchrom6s3.pdf vignetteTitles: chrom6TkNN.pdf, chrom6T.pdf, evalkNN6.pdf, MicroArray Chromosome Analysis Tool, Slidingchrom6s3.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/macat/inst/doc/macat.R Package: maCorrPlot Version: 1.30.0 Depends: lattice Imports: graphics, grDevices, lattice, stats License: GPL (>= 2) MD5sum: b2376597765fcc59152eb7326b1562c1 NeedsCompilation: no Title: Visualize artificial correlation in microarray data Description: Graphically displays correlation in microarray data that is due to insufficient normalization biocViews: Microarray, Preprocessing, Visualization Author: Alexander Ploner Maintainer: Alexander Ploner URL: http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed&pubmedid=15799785 source.ver: src/contrib/maCorrPlot_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/maCorrPlot_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/maCorrPlot_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/maCorrPlot_1.30.0.tgz vignettes: vignettes/maCorrPlot/inst/doc/maCorrPlot.pdf vignetteTitles: maCorrPlot Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maCorrPlot/inst/doc/maCorrPlot.R Package: maDB Version: 1.32.0 Depends: R (>= 2.6.0), Biobase (>= 2.5.5), affy (>= 1.23.4), pgUtils (>= 1.23.2), limma (>= 1.8.0), methods Suggests: annaffy (>= 1.6.2), biomaRt (>= 1.8.2), geneplotter License: LGPL (>= 2) MD5sum: e01f7a112a2423d25e490f6c145f7c9e NeedsCompilation: no Title: Microarray database and utility functions for microarray data analysis. Description: maDB allows to create a simple microarray database to store microarray experiments and annotation data into it. Affymetrix GeneChip expression values as well as values from two color microarrays can be stored into the database. Whole experiments or subsets from a experiment (or also values for a subset of genes in a subset of microarrays) can be fetched back to R. Additionally maDB provides different utility functions for the microarray data analysis like functions to draw MA plots or volcano plots with the data points color coded according to the local point density or functions that allow a replicate handling of miroarrays. biocViews: Microarray,TwoChannel,OneChannel,Visualization Author: Johannes Rainer Maintainer: Johannes Rainer source.ver: src/contrib/maDB_1.32.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/maDB_1.32.0.tgz vignettes: vignettes/maDB/inst/doc/maDB-015.pdf, vignettes/maDB/inst/doc/maDB-016.pdf, vignettes/maDB/inst/doc/maDB.pdf vignetteTitles: maDB-015.pdf, maDB-016.pdf, maDB.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: made4 Version: 1.34.0 Depends: ade4, RColorBrewer,gplots,scatterplot3d Suggests: affy License: Artistic-2.0 MD5sum: 423950d75d7a3f24f847d19c725b0b94 NeedsCompilation: no Title: Multivariate analysis of microarray data using ADE4 Description: Multivariate data analysis and graphical display of microarray data. Functions include between group analysis and coinertia analysis. It contains functions that require ADE4. biocViews: Bioinformatics, Clustering, Classification, MultipleComparisons Author: Aedin Culhane Maintainer: Aedin Culhane URL: http://www.hsph.harvard.edu/researchers/aculhane.html source.ver: src/contrib/made4_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/made4_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/made4_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/made4_1.34.0.tgz vignettes: vignettes/made4/inst/doc/html3D.pdf, vignettes/made4/inst/doc/introduction.pdf vignetteTitles: html3D.pdf, introduction.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/made4/inst/doc/introduction.R dependsOnMe: bgafun Package: maigesPack Version: 1.24.0 Depends: R (>= 2.10), convert, graph, limma, marray, methods Suggests: amap, annotate, class, e1071, MASS, multtest, OLIN, R2HTML, rgl, som License: GPL (>= 2) Archs: i386, x64 MD5sum: d08af4e89d0e54ba64de3ac8bcb25027 NeedsCompilation: yes Title: Functions to handle cDNA microarray data, including several methods of data analysis Description: This package uses functions of various other packages together with other functions in a coordinated way to handle and analyse cDNA microarray data biocViews: Microarray, TwoChannel, Preprocessing, ConnectTools, DifferentialExpression, Clustering, Classification, GraphsAndNetworks Author: Gustavo H. Esteves , with contributions from Roberto Hirata Jr , E. Jordao Neves , Elier B. Cristo , Ana C. Simoes and Lucas Fahham Maintainer: Gustavo H. Esteves URL: http://www.maiges.org/en/software/ source.ver: src/contrib/maigesPack_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/maigesPack_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/maigesPack_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/maigesPack_1.24.0.tgz vignettes: vignettes/maigesPack/inst/doc/maigesPack_tutorial.pdf vignetteTitles: maigesPack Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maigesPack/inst/doc/maigesPack_tutorial.R Package: makecdfenv Version: 1.36.0 Depends: R (>= 2.6.0), methods, affyio Imports: Biobase, affy, methods, stats, utils, zlibbioc License: GPL (>= 2) Archs: i386, x64 MD5sum: 50cd4dce2e39b34f3601c07b26a576ca NeedsCompilation: yes Title: CDF Environment Maker Description: This package has two functions. One reads a Affymetrix chip description file (CDF) and creates a hash table environment containing the location/probe set membership mapping. The other creates a package that automatically loads that environment. biocViews: OneChannel, DataImport, Preprocessing Author: Rafael A. Irizarry , Laurent Gautier , Wolfgang Huber , Ben Bolstad Maintainer: James W. MacDonald source.ver: src/contrib/makecdfenv_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/makecdfenv_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/makecdfenv_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/makecdfenv_1.36.0.tgz vignettes: vignettes/makecdfenv/inst/doc/makecdfenv.pdf vignetteTitles: makecdfenv primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/makecdfenv/inst/doc/makecdfenv.R dependsOnMe: altcdfenvs Package: MANOR Version: 1.32.0 Depends: R (>= 2.10), GLAD Imports: GLAD, graphics, grDevices, stats, utils License: GPL-2 Archs: i386, x64 MD5sum: 72d9f783976fc5c72e4a43d2a4fe57b0 NeedsCompilation: yes Title: CGH Micro-Array NORmalization Description: Importation, normalization, visualization, and quality control functions to correct identified sources of variability in array-CGH experiments. biocViews: Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, CopyNumberVariants Author: Pierre Neuvial , Philippe Hupe Maintainer: Pierre Neuvial URL: http://bioinfo.curie.fr/projects/manor/index.html source.ver: src/contrib/MANOR_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MANOR_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MANOR_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MANOR_1.32.0.tgz vignettes: vignettes/MANOR/inst/doc/MANOR.pdf vignetteTitles: MANOR overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MANOR/inst/doc/MANOR.R Package: manta Version: 1.6.1 Depends: R (>= 1.8.0), methods, edgeR (>= 2.5.13) Imports: Hmisc Suggests: RSQLite, plotrix License: Artistic-2.0 MD5sum: 1f5a6db058ee615e0589161c72bc9072 NeedsCompilation: no Title: Microbial Assemblage Normalized Transcript Analysis Description: Tools for robust comparative metatranscriptomics. biocViews: DifferentialExpression, RNAseq, Genetics, GeneExpression, Bioinformatics, HighThroughputSequencing, QualityControl, DataImport, Visualization Author: Ginger Armbrust, Adrian Marchetti, David M. Schruth Maintainer: Chris Berthiaume , Adrian Marchetti URL: http://manta.ocean.washington.edu/ source.ver: src/contrib/manta_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/manta_1.6.1.zip win64.binary.ver: bin/windows64/contrib/2.16/manta_1.6.1.zip mac.binary.ver: bin/macosx/contrib/2.16/manta_1.6.1.tgz vignettes: vignettes/manta/inst/doc/manta.pdf vignetteTitles: manta hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/manta/inst/doc/manta.R Package: MantelCorr Version: 1.30.0 Depends: R (>= 2.10) Imports: stats License: GPL (>= 2) MD5sum: c0a679d6dd1ae10af8414117b018a06b NeedsCompilation: no Title: Compute Mantel Cluster Correlations Description: Computes Mantel cluster correlations from a (p x n) numeric data matrix (e.g. microarray gene-expression data). biocViews: Bioinformatics, Clustering Author: Brian Steinmeyer and William Shannon Maintainer: Brian Steinmeyer source.ver: src/contrib/MantelCorr_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MantelCorr_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MantelCorr_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MantelCorr_1.30.0.tgz vignettes: vignettes/MantelCorr/inst/doc/MantelCorrVignette.pdf vignetteTitles: MantelCorrVignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MantelCorr/inst/doc/MantelCorrVignette.R Package: marray Version: 1.38.0 Depends: R (>= 2.10.0), limma, methods Suggests: tkWidgets License: LGPL MD5sum: e8e13d83659a2a8c03f73730c3e512d7 NeedsCompilation: no Title: Exploratory analysis for two-color spotted microarray data Description: Class definitions for two-color spotted microarray data. Fuctions for data input, diagnostic plots, normalization and quality checking. biocViews: Microarray, TwoChannel, Preprocessing Author: Yee Hwa (Jean) Yang with contributions from Agnes Paquet and Sandrine Dudoit. Maintainer: Yee Hwa (Jean) Yang URL: http://www.maths.usyd.edu.au/u/jeany/ source.ver: src/contrib/marray_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/marray_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/marray_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/marray_1.38.0.tgz vignettes: vignettes/marray/inst/doc/ExampleHTML.pdf, vignettes/marray/inst/doc/marrayClasses.pdf, vignettes/marray/inst/doc/marrayClassesShort.pdf, vignettes/marray/inst/doc/marrayInput.pdf, vignettes/marray/inst/doc/marrayNorm.pdf, vignettes/marray/inst/doc/marray.pdf, vignettes/marray/inst/doc/marrayPlots.pdf, vignettes/marray/inst/doc/widget1.pdf vignetteTitles: ExampleHTML.pdf, marrayClasses Overview, marrayClasses Tutorial (short), marrayInput Introduction, marray Normalization, marray Overview, marrayPlots Overview, widget1.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/marray/inst/doc/marrayClasses.R, vignettes/marray/inst/doc/marrayClassesShort.R, vignettes/marray/inst/doc/marrayInput.R, vignettes/marray/inst/doc/marrayNorm.R, vignettes/marray/inst/doc/marrayPlots.R, vignettes/marray/inst/doc/marray.R dependsOnMe: CGHbase, convert, dyebias, maigesPack, MineICA, nnNorm, OLIN, stepNorm, TurboNorm importsMe: arrayQuality, nnNorm, OLIN, OLINgui, piano, plrs, sigaR, stepNorm, timecourse suggestsMe: Agi4x44PreProcess, DEGraph, Mfuzz Package: maSigPro Version: 1.32.3 Depends: R (>= 2.3.1), stats, Biobase, MASS Imports: Biobase, graphics, grDevices, limma, Mfuzz, stats, utils, MASS License: GPL (>= 2) MD5sum: c6030a08e9f15e72f1ddba1c41fe5979 NeedsCompilation: no Title: Significant Gene Expression Profile Differences in Time Course Microarray Data Description: maSigPro is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray experiments. biocViews: Microarray, DifferentialExpression, TimeCourse Author: Ana Conesa , Maria Jose Nueda Maintainer: Maria Jose Nueda URL: http://bioinfo.cipf.es/ source.ver: src/contrib/maSigPro_1.32.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/maSigPro_1.32.3.zip win64.binary.ver: bin/windows64/contrib/2.16/maSigPro_1.32.3.zip mac.binary.ver: bin/macosx/contrib/2.16/maSigPro_1.32.3.tgz vignettes: vignettes/maSigPro/inst/doc/maSigPro.pdf, vignettes/maSigPro/inst/doc/maSigProUsersGuide.pdf vignetteTitles: maSigPro Vignette, maSigProUsersGuide.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maSigPro/inst/doc/maSigPro.R, vignettes/maSigPro/inst/doc/maSigPro-tutorial.R suggestsMe: oneChannelGUI Package: maskBAD Version: 1.4.0 Depends: R (>= 2.10), gcrma (>= 2.27.1), affy Suggests: hgu95av2probe License: GPL version 2 or newer MD5sum: 9222861542d7f2044ed2acd1be7aa049 NeedsCompilation: no Title: Masking probes with binding affinity differences Description: Package includes functions to analyze and mask microarray expression data. Author: Michael Dannemann Maintainer: Michael Dannemann source.ver: src/contrib/maskBAD_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/maskBAD_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/maskBAD_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/maskBAD_1.4.0.tgz vignettes: vignettes/maskBAD/inst/doc/maskBAD.pdf vignetteTitles: Package maskBAD hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maskBAD/inst/doc/maskBAD.R Package: MassArray Version: 1.12.0 Depends: R (>= 2.10.0), methods Imports: graphics, grDevices, methods, stats, utils License: GPL (>=2) MD5sum: 8c296927d32fd8a7c4988eea3455fce2 NeedsCompilation: no Title: Analytical Tools for MassArray Data Description: This package is designed for the import, quality control, analysis, and visualization of methylation data generated using Sequenom's MassArray platform. The tools herein contain a highly detailed amplicon prediction for optimal assay design. Also included are quality control measures of data, such as primer dimer and bisulfite conversion efficiency estimation. Methylation data are calculated using the same algorithms contained in the EpiTyper software package. Additionally, automatic SNP-detection can be used to flag potentially confounded data from specific CG sites. Visualization includes barplots of methylation data as well as UCSC Genome Browser-compatible BED tracks. Multiple assays can be positionally combined for integrated analysis. biocViews: DNAMethylation, SNP, MassSpectrometry, Genetics, DataImport, Visualization Author: Reid F. Thompson , John M. Greally Maintainer: Reid F. Thompson source.ver: src/contrib/MassArray_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MassArray_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MassArray_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MassArray_1.12.0.tgz vignettes: vignettes/MassArray/inst/doc/conversion.pdf, vignettes/MassArray/inst/doc/MassArray.pdf vignetteTitles: conversion.pdf, 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MassArray/inst/doc/MassArray.R Package: MassSpecWavelet Version: 1.26.0 Depends: waveslim Suggests: xcms, caTools License: LGPL (>= 2) Archs: i386, x64 MD5sum: 4d7b8d7992ad37331008bd2c341da885 NeedsCompilation: yes Title: Mass spectrum processing by wavelet-based algorithms Description: Processing Mass Spectrometry spectrum by using wavelet based algorithm biocViews: MassSpectrometry, Proteomics Author: Pan Du, Warren Kibbe, Simon Lin Maintainer: Pan Du source.ver: src/contrib/MassSpecWavelet_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MassSpecWavelet_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MassSpecWavelet_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MassSpecWavelet_1.26.0.tgz vignettes: vignettes/MassSpecWavelet/inst/doc/MassSpecWavelet.pdf vignetteTitles: MassSpecWavelet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MassSpecWavelet/inst/doc/MassSpecWavelet.R suggestsMe: xcms Package: matchBox Version: 1.2.0 Depends: R (>= 2.8.0) License: Artistic-2.0 MD5sum: b0a47d31dcb39bcdb7489533d9d61baa NeedsCompilation: no Title: Utilities to compute, compare, and plot the agreement between ordered vectors of features (ie. distinct genomic experiments). The package includes Correspondence-At-the-TOP (CAT) analysis. Description: The matchBox package enables comparing ranked vectors of features, merging multiple datasets, removing redundant features, using CAT-plots and Venn diagrams, and computing statistical significance. biocViews: Software, Annotation, Microarray, MultipleComparisons, Visualization Author: Luigi Marchionni , Anuj Gupta Maintainer: Luigi Marchionni , Anuj Gupta source.ver: src/contrib/matchBox_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/matchBox_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/matchBox_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/matchBox_1.2.0.tgz vignettes: vignettes/matchBox/inst/doc/matchBox.pdf vignetteTitles: Working with the matchBox package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/matchBox/inst/doc/matchBox.R Package: MBCB Version: 1.14.0 Depends: R (>= 2.9.0), tcltk, tcltk2 Imports: preprocessCore, stats, utils License: GPL (>= 2) MD5sum: 546f95845fdccbece4ee7bc19c14bd90 NeedsCompilation: no Title: MBCB (Model-based Background Correction for Beadarray) Description: This package provides a model-based background correction method, which incorporates the negative control beads to pre-process Illumina BeadArray data. biocViews: Microarray, Preprocessing Author: Yang Xie Maintainer: Jeff Allen URL: http://www.utsouthwestern.edu source.ver: src/contrib/MBCB_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MBCB_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MBCB_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MBCB_1.14.0.tgz vignettes: vignettes/MBCB/inst/doc/MBCB.pdf vignetteTitles: MBCB hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MBCB/inst/doc/MBCB.R Package: mBPCR Version: 1.14.0 Depends: oligoClasses, SNPchip Imports: Biobase Suggests: xtable License: GPL (>= 2) MD5sum: 7ac51f0b5f0616624fae7ab9f3843fee NeedsCompilation: no Title: Bayesian Piecewise Constant Regression for DNA copy number estimation Description: Estimates the DNA copy number profile using mBPCR to detect regions with copy number changes biocViews: aCGH, SNP, Microarray, CopyNumberVariants, Bioinformatics Author: P.M.V. Rancoita , with contributions from M. Hutter Maintainer: P.M.V. Rancoita URL: http://www.idsia.ch/~paola/mBPCR source.ver: src/contrib/mBPCR_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/mBPCR_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/mBPCR_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/mBPCR_1.14.0.tgz vignettes: vignettes/mBPCR/inst/doc/mBPCR.pdf vignetteTitles: mBPCR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mBPCR/inst/doc/mBPCR.R Package: mcaGUI Version: 1.8.0 Depends: lattice, MASS, proto, foreign, gWidgets(>= 0.0-36), gWidgetsRGtk2(>= 0.0-53), OTUbase, vegan, bpca Enhances: iplots, reshape, ggplot2, cairoDevice, OTUbase License: GPL (>= 2) MD5sum: e791b597e29e2710dcc5bcc5e53556a7 NeedsCompilation: no Title: Microbial Community Analysis GUI Description: Microbial community analysis GUI for R using gWidgets. biocViews: GUI, Visualization, Bioinformatics, Clustering, Sequencing Author: Wade K. Copeland, Vandhana Krishnan, Daniel Beck, Matt Settles, James Foster, Kyu-Chul Cho, Mitch Day, Roxana Hickey, Ursel M.E. Schutte, Xia Zhou, Chris Williams, Larry J. Forney, Zaid Abdo, Poor Man's GUI (PMG) base code by John Verzani with contributions by Yvonnick Noel Maintainer: Wade K. Copeland URL: http://www.ibest.uidaho.edu/ibest/index.php source.ver: src/contrib/mcaGUI_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/mcaGUI_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/mcaGUI_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/mcaGUI_1.8.0.tgz vignettes: vignettes/mcaGUI/inst/doc/An_Introduction_and_User_Guide_for_mcaGUI.pdf vignetteTitles: An_Introduction_and_User_Guide_for_mcaGUI.pdf hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: MCRestimate Version: 2.16.0 Depends: R (>= 2.7.2), golubEsets (>= 1.4.6) Imports: e1071 (>= 1.5-12), pamr (>= 1.22), randomForest (>= 3.9-6), RColorBrewer (>= 0.1-3), Biobase (>= 2.5.5), graphics, grDevices, stats, utils Suggests: xtable (>= 1.2-1), ROC (>= 1.8.0), genefilter (>= 1.12.0), gpls (>= 1.6.0) License: GPL (>= 2) MD5sum: 88975473afe458ffab0c6adfdbad287e NeedsCompilation: no Title: Misclassification error estimation with cross-validation Description: This package includes a function for combining preprocessing and classification methods to calculate misclassification errors biocViews: Bioinformatics, Classification Author: Marc Johannes, Markus Ruschhaupt, Holger Froehlich, Ulrich Mansmann, Andreas Buness, Patrick Warnat, Wolfgang Huber, Axel Benner, Tim Beissbarth Maintainer: Marc Johannes source.ver: src/contrib/MCRestimate_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MCRestimate_2.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MCRestimate_2.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MCRestimate_2.16.0.tgz vignettes: vignettes/MCRestimate/inst/doc/UsingMCRestimate.pdf vignetteTitles: HOW TO use MCRestimate hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MCRestimate/inst/doc/UsingMCRestimate.R Package: mdqc Version: 1.22.0 Depends: R (>= 2.2.1), cluster, MASS License: LGPL (>= 2) MD5sum: b46c794abe34609536c8be138e77b914 NeedsCompilation: no Title: Mahalanobis Distance Quality Control for microarrays Description: MDQC is a multivariate quality assessment method for microarrays based on quality control (QC) reports. The Mahalanobis distance of an array's quality attributes is used to measure the similarity of the quality of that array against the quality of the other arrays. Then, arrays with unusually high distances can be flagged as potentially low-quality. biocViews: Microarray, QualityControl Author: Justin Harrington Maintainer: Gabriela Cohen-Freue source.ver: src/contrib/mdqc_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/mdqc_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/mdqc_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/mdqc_1.22.0.tgz vignettes: vignettes/mdqc/inst/doc/mdqcvignette.pdf vignetteTitles: Introduction to MDQC hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mdqc/inst/doc/mdqcvignette.R importsMe: arrayMvout Package: MeasurementError.cor Version: 1.32.0 License: LGPL MD5sum: 8867b98163cd09e0b0ac943a34a4f4dd NeedsCompilation: no Title: Measurement Error model estimate for correlation coefficient Description: Two-stage measurement error model for correlation estimation with smaller bias than the usual sample correlation biocViews: Bioinformatics Author: Beiying Ding Maintainer: Beiying Ding source.ver: src/contrib/MeasurementError.cor_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MeasurementError.cor_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MeasurementError.cor_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MeasurementError.cor_1.32.0.tgz vignettes: vignettes/MeasurementError.cor/inst/doc/MeasurementError.cor.pdf vignetteTitles: MeasurementError.cor Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: MEDIPS Version: 1.10.0 Depends: R (>= 2.12.0), BSgenome, DNAcopy Imports: Biostrings, BSgenome, Rsamtools, graphics, gtools, IRanges, methods, stats, utils, GenomicRanges, edgeR, GenomicFeatures, DNAcopy, biomaRt, rtracklayer Suggests: BSgenome, BSgenome.Hsapiens.UCSC.hg19, MEDIPSData License: GPL (>=2) MD5sum: 0a607287cca43e842786cfba6ad8215c NeedsCompilation: no Title: (MeD)IP-seq data analysis Description: MEDIPS was developed for analyzing data derived from methylated DNA immunoprecipitation (MeDIP) experiments followed by sequencing (MeDIP-seq). However, MEDIPS provides several functionalities for the analysis of other kinds of quantitative sequencing data (e.g. ChIP-seq, MBD-seq, CMS-seq and others) including calculation of differential coverage between groups of samples as well as saturation and correlation analyses. biocViews: Sequencing, DNAMethylation, CpGIsland, DifferentialExpression, HighThroughputSequencing, ChIPseq, Preprocessing, QualityControl, Visualization Author: Lukas Chavez, Matthias Lienhard, Joern Dietrich Maintainer: Lukas Chavez source.ver: src/contrib/MEDIPS_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MEDIPS_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MEDIPS_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MEDIPS_1.10.0.tgz vignettes: vignettes/MEDIPS/inst/doc/MEDIPS.pdf vignetteTitles: MEDIPS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MEDIPS/inst/doc/MEDIPS.R Package: MEDME Version: 1.20.0 Depends: R (>= 2.15), grDevices, graphics, methods, stats, utils Imports: Biostrings, MASS, drc Suggests: BSgenome.Hsapiens.UCSC.hg18, BSgenome.Mmusculus.UCSC.mm9 License: GPL (>= 2) Archs: i386, x64 MD5sum: 5fd91511100f17ec6ff9d9dd5923c138 NeedsCompilation: yes Title: Modelling Experimental Data from MeDIP Enrichment Description: Description: MEDME allows the prediction of absolute and relative methylation levels based on measures obtained by MeDIP-microarray experiments biocViews: Microarray, CpGIsland, DNAMethylation Author: Mattia Pelizzola and Annette Molinaro Maintainer: Mattia Pelizzola source.ver: src/contrib/MEDME_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MEDME_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MEDME_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MEDME_1.20.0.tgz vignettes: vignettes/MEDME/inst/doc/MEDME.pdf vignetteTitles: MEDME.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MEDME/inst/doc/MEDME.R Package: MergeMaid Version: 2.32.0 Depends: R (>= 2.10.0), survival, Biobase, MASS, methods License: GPL (>= 2) MD5sum: 6c3c7245493ef8f0f96adb21da256613 NeedsCompilation: no Title: Merge Maid Description: The functions in this R extension are intended for cross-study comparison of gene expression array data. Required from the user is gene expression matrices, their corresponding gene-id vectors and other useful information, and they could be 'list','matrix', or 'ExpressionSet'. The main function is 'mergeExprs' which transforms the input objects into data in the merged format, such that common genes in different datasets can be easily found. And the function 'intcor' calculate the correlation coefficients. Other functions use the output from 'modelOutcome' to graphically display the results and cross-validate associations of gene expression data with survival. biocViews: Microarray, DifferentialExpression, Visualization Author: Xiaogang Zhong Leslie Cope Elizabeth Garrett Giovanni Parmigiani Maintainer: Xiaogang Zhong URL: http://astor.som.jhmi.edu/MergeMaid source.ver: src/contrib/MergeMaid_2.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MergeMaid_2.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MergeMaid_2.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MergeMaid_2.32.0.tgz vignettes: vignettes/MergeMaid/inst/doc/MergeMaid.pdf vignetteTitles: MergeMaid primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MergeMaid/inst/doc/MergeMaid.R importsMe: metaArray, XDE suggestsMe: oneChannelGUI Package: metaArray Version: 1.38.0 Imports: Biobase, MergeMaid, graphics, stats License: LGPL-2 Archs: i386, x64 MD5sum: b884ebb992542400bc7ce2e0948364de NeedsCompilation: yes Title: Integration of Microarray Data for Meta-analysis Description: 1) Data transformation for meta-analysis of microarray Data: Transformation of gene expression data to signed probability scale (MCMC/EM methods) 2) Combined differential expression on raw scale: Weighted Z-score after stabilizing mean-variance relation within platform biocViews: Microarray, Bioinformatics, DifferentialExpression Author: Debashis Ghosh Hyungwon Choi Maintainer: Hyungwon Choi source.ver: src/contrib/metaArray_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/metaArray_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/metaArray_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/metaArray_1.38.0.tgz vignettes: vignettes/metaArray/inst/doc/metaArray.pdf vignetteTitles: metaArray Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metaArray/inst/doc/metaArray.R suggestsMe: oneChannelGUI Package: metagenomeSeq Version: 1.0.6 Depends: R(>= 3.0), Biobase, limma, matrixStats, methods, RColorBrewer, gplots Suggests: annotate License: Artistic-2.0 MD5sum: 3b3a91687d14b3fbeb66da1f5f85ff95 NeedsCompilation: no Title: Statistical analysis for sparse high-throughput sequencing Description: metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations. biocViews: Bioinformatics, DifferentialExpression, Metagenomics, Visualization Author: Joseph Nathaniel Paulson, Mihai Pop, Hector Corrada-Bravo Maintainer: Joseph Paulson URL: http://cbcb.umd.edu/software/metagenomeSeq source.ver: src/contrib/metagenomeSeq_1.0.6.tar.gz win.binary.ver: bin/windows/contrib/2.16/metagenomeSeq_1.0.6.zip win64.binary.ver: bin/windows64/contrib/2.16/metagenomeSeq_1.0.6.zip mac.binary.ver: bin/macosx/contrib/2.16/metagenomeSeq_1.0.6.tgz vignettes: vignettes/metagenomeSeq/inst/doc/metagenomeSeq.pdf vignetteTitles: Analyzing metagenomic data with metagenomeSeq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metagenomeSeq/inst/doc/metagenomeSeq.R Package: metahdep Version: 1.18.0 Depends: R (>= 2.10), methods Suggests: affyPLM License: GPL-3 Archs: i386, x64 MD5sum: 0975484c05037d92b69bb29daab5c386 NeedsCompilation: yes Title: Hierarchical Dependence in Meta-Analysis Description: Tools for meta-analysis in the presence of hierarchical (and/or sampling) dependence, including with gene expression studies biocViews: Microarray, Bioinformatics, DifferentialExpression Author: John R. Stevens, Gabriel Nicholas Maintainer: John R. Stevens source.ver: src/contrib/metahdep_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/metahdep_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/metahdep_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/metahdep_1.18.0.tgz vignettes: vignettes/metahdep/inst/doc/metahdep.pdf vignetteTitles: metahdep Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metahdep/inst/doc/metahdep.R Package: methVisual Version: 1.12.0 Depends: R (>= 2.11.0), Biostrings(>= 2.4.8), plotrix,gsubfn, grid,sqldf Imports: Biostrings, ca, graphics, grDevices, grid, gridBase, IRanges, stats, utils License: GPL (>= 2) MD5sum: bdefed962a94b56302da8d10aeed41fc NeedsCompilation: no Title: Methods for visualization and statistics on DNA methylation data Description: The package 'methVisual' allows the visualization of DNA methylation data after bisulfite sequencing. biocViews: Bioinformatics, DNAMethylation, Clustering, Classification Author: A. Zackay, C. Steinhoff Maintainer: Arie Zackay source.ver: src/contrib/methVisual_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/methVisual_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/methVisual_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/methVisual_1.12.0.tgz vignettes: vignettes/methVisual/inst/doc/methVisual.pdf vignetteTitles: Introduction to methVisual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methVisual/inst/doc/methVisual.R Package: methyAnalysis Version: 1.2.0 Depends: R (>= 2.10), grid, IRanges, Biobase (>= 2.5.5), org.Hs.eg.db Imports: lumi, methylumi, Gviz, genoset, GenomicRanges, IRanges, rtracklayer, GenomicFeatures, annotate, Biobase (>= 2.5.5), AnnotationDbi, genefilter, biomaRt, methods Suggests: IlluminaHumanMethylation450k.db, TxDb.Hsapiens.UCSC.hg19.knownGene License: Artistic-2.0 MD5sum: 6b2b7fc09b1f41742017797e7c263d03 NeedsCompilation: no Title: DNA methylation data analysis and visualization Description: The methyAnalysis package aims for the DNA methylation data analysis and visualization. A new class is defined to keep the chromosome location information together with the data. The current version of the package mainly focus on analyzing the Illumina Infinium methylation array data, but most methods can be generalized to other methylation array or sequencing data. biocViews: Microarray, DNAMethylation, Visualization Author: Pan Du, Richard Bourgon Maintainer: Pan Du source.ver: src/contrib/methyAnalysis_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/methyAnalysis_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/methyAnalysis_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/methyAnalysis_1.2.0.tgz vignettes: vignettes/methyAnalysis/inst/doc/methyAnalysis.pdf vignetteTitles: An Introduction to the methyAnalysis package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methyAnalysis/inst/doc/methyAnalysis.R Package: MethylSeekR Version: 1.0.1 Depends: rtracklayer (>= 1.16.3), parallel (>= 2.15.1), mhsmm (>= 0.4.4) Imports: IRanges (>= 1.16.3), BSgenome (>= 1.26.1), GenomicRanges (>= 1.10.5), geneplotter (>= 1.34.0), graphics (>= 2.15.2), grDevices (>= 2.15.2), parallel (>= 2.15.2), stats (>= 2.15.2), utils (>= 2.15.2) Suggests: BSgenome.Hsapiens.UCSC.hg18 License: GPL (>=2) MD5sum: b7341f4fd929c287ff9b419f34bff7a4 NeedsCompilation: no Title: Segmentation of Bis-seq data Description: This is a package for the discovery of regulatory regions from Bis-seq data biocViews: HighThroughputSequencing, Methylseq, DNAMethylation Author: Lukas Burger, Dimos Gaidatzis, Dirk Schubeler and Michael Stadler Maintainer: Lukas Burger source.ver: src/contrib/MethylSeekR_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/MethylSeekR_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/MethylSeekR_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/MethylSeekR_1.0.1.tgz vignettes: vignettes/MethylSeekR/inst/doc/MethylSeekR.pdf vignetteTitles: MethylSeekR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MethylSeekR/inst/doc/MethylSeekR.R Package: methylumi Version: 2.6.1 Depends: Biobase, methods, R (>= 2.13), scales, reshape2, ggplot2 Imports: Biobase, graphics, lattice, annotate, genefilter, AnnotationDbi, stats4, BiocGenerics, AnnotationForge, minfi Suggests: lumi, lattice, limma, xtable, IlluminaHumanMethylation27k.db (>= 1.4.4), IlluminaHumanMethylation450k.db, SQN, GenomicRanges, MASS, matrixStats, parallel, rtracklayer, Biostrings, FDb.InfiniumMethylation.hg19 License: GPL-2 MD5sum: 3000dff3a32dac39c751f69648894d69 NeedsCompilation: no Title: Handle Illumina methylation data Description: This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included. biocViews: DNAMethylation, TwoChannel, Preprocessing, QualityControl, CpGIsland Author: Sean Davis, Pan Du, Sven Bilke, Tim Triche, Jr., Moiz Bootwalla Maintainer: Sean Davis source.ver: src/contrib/methylumi_2.6.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/methylumi_2.6.1.zip win64.binary.ver: bin/windows64/contrib/2.16/methylumi_2.6.1.zip mac.binary.ver: bin/macosx/contrib/2.16/methylumi_2.6.1.tgz vignettes: vignettes/methylumi/inst/doc/methylumi.pdf vignetteTitles: An Introduction to the methylumi package hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methylumi/inst/doc/methylumi.R dependsOnMe: wateRmelon importsMe: ffpe, lumi, methyAnalysis Package: Mfuzz Version: 2.18.0 Depends: R (>= 2.5.0), Biobase (>= 2.5.5), e1071 Imports: tcltk, tkWidgets Suggests: marray License: GPL-2 MD5sum: 9d9c01910b23a15165898e75cb7809ad NeedsCompilation: no Title: Soft clustering of time series gene expression data Description: Package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface) biocViews: Microarray, Clustering, TimeCourse, Preprocessing, Visualization Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/Mfuzz/ source.ver: src/contrib/Mfuzz_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Mfuzz_2.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Mfuzz_2.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Mfuzz_2.18.0.tgz vignettes: vignettes/Mfuzz/inst/doc/MfuzzguiScreenshot.pdf, vignettes/Mfuzz/inst/doc/Mfuzz.pdf, vignettes/Mfuzz/inst/doc/yeasttable3.pdf vignetteTitles: MfuzzguiScreenshot.pdf, Introduction to Mfuzz, yeasttable3.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Mfuzz/inst/doc/Mfuzz.R dependsOnMe: cycle importsMe: maSigPro Package: mgsa Version: 1.8.1 Depends: R (>= 2.14.0), methods, gplots Imports: graphics, stats, utils Suggests: DBI, RSQLite, GO.db License: Artistic-2.0 Archs: i386, x64 MD5sum: 3ff3734b82698da4550d1fbfb0ed4cd4 NeedsCompilation: yes Title: Model-based gene set analysis Description: Model-based Gene Set Analysis (MGSA) is a Bayesian modeling approach for gene set enrichment. The package mgsa implements MGSA and tools to use MGSA together with the Gene Ontology. biocViews: Pathways, GO, GeneSetEnrichment Author: Sebastian Bauer , Julien Gagneur Maintainer: Sebastian Bauer source.ver: src/contrib/mgsa_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/mgsa_1.8.1.zip win64.binary.ver: bin/windows64/contrib/2.16/mgsa_1.8.1.zip mac.binary.ver: bin/macosx/contrib/2.16/mgsa_1.8.1.tgz vignettes: vignettes/mgsa/inst/doc/mgsa.pdf vignetteTitles: Overview of the mgsa package. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mgsa/inst/doc/mgsa.R suggestsMe: gCMAP Package: MiChip Version: 1.14.0 Depends: R (>= 2.3.0), Biobase Imports: Biobase License: GPL (>= 2) MD5sum: 07bb2a7a91260645fdf2ab613bda1526 NeedsCompilation: no Title: MiChip Parsing and Summarizing Functions Description: This package takes the MiChip miRNA microarray .grp scanner output files and parses these out, providing summary and plotting functions to analyse MiChip hybridizations. A set of hybridizations is packaged into an ExpressionSet allowing it to be used by other BioConductor packages. biocViews: Microarray, Preprocessing Author: Jonathon Blake Maintainer: Jonathon Blake source.ver: src/contrib/MiChip_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MiChip_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MiChip_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MiChip_1.14.0.tgz vignettes: vignettes/MiChip/inst/doc/MiChip.pdf vignetteTitles: MiChip miRNA Microarray Processing hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MiChip/inst/doc/MiChip.R Package: microRNA Version: 1.18.0 Depends: R (>= 2.10) Imports: Biostrings (>= 2.11.32) Suggests: Biostrings (>= 2.11.32) Enhances: Rlibstree License: Artistic-2.0 MD5sum: 43afee178860ed5fada0f8df563e21f6 NeedsCompilation: no Title: Data and functions for dealing with microRNAs Description: Different data resources for microRNAs and some functions for manipulating them. biocViews: Infrastructure, SequenceAnnotation, SequenceMatching Author: R. Gentleman, S. Falcon Maintainer: "James F. Reid" source.ver: src/contrib/microRNA_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/microRNA_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/microRNA_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/microRNA_1.18.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE suggestsMe: MmPalateMiRNA, rtracklayer Package: MineICA Version: 1.0.0 Depends: R (>= 2.10), Biobase, plyr, ggplot2, scales, foreach, xtable, biomaRt, gtools, GOstats, cluster, marray, mclust, RColorBrewer, colorspace, igraph, Rgraphviz, graph, annotate, Hmisc, fastICA, JADE, methods Imports: AnnotationDbi, lumi, fpc, lumiHumanAll.db Suggests: biomaRt, GOstats, cluster, hgu133a.db, mclust, igraph, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerVDX Enhances: doMC License: GPL-2 MD5sum: 5bb8effa329c27beb44efa4a8e3c143b NeedsCompilation: no Title: Analysis of an ICA decomposition obtained on genomics data Description: The goal of MineICA is to make easier the interpretation of the interpretation of a decomposition obtained by Independent Component Analysis on transcriptomic data. It helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph. Author: Anne Biton Maintainer: Anne Biton source.ver: src/contrib/MineICA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MineICA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MineICA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MineICA_1.0.0.tgz vignettes: vignettes/MineICA/inst/doc/MineICA.pdf vignetteTitles: MineICA: Independent component analysis of genomic data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MineICA/inst/doc/MineICA.R Package: minet Version: 3.14.0 Depends: infotheo License: CC BY-NC-SA 3.0 Archs: i386, x64 MD5sum: ce46f0eb6c4a61b2c10d3219e045f6bf NeedsCompilation: yes Title: Mutual Information NETworks Description: This package implements various algorithms for inferring mutual information networks from data. biocViews: Microarray, GraphsAndNetworks, NetworkAnalysis, NetworkInference Author: Patrick E. Meyer, Frederic Lafitte, Gianluca Bontempi Maintainer: Patrick E. Meyer URL: http://minet.meyerp.com source.ver: src/contrib/minet_3.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/minet_3.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/minet_3.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/minet_3.14.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: BUS, geNetClassifier, netresponse suggestsMe: CNORfeeder, predictionet Package: minfi Version: 1.6.0 Depends: methods, BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), lattice, reshape, GenomicRanges, Biostrings, utils Imports: BiocGenerics, beanplot, RColorBrewer, nor1mix, siggenes, limma, preprocessCore, illuminaio, matrixStats, mclust Suggests: IlluminaHumanMethylation450kmanifest (>= 0.2.0), minfiData (>= 0.2.0), RUnit, digest License: Artistic-2.0 MD5sum: a1172ac92162bed91e02364ac5e57c0f NeedsCompilation: no Title: Analyze Illumina's 450k methylation arrays Description: Tools for analyzing and visualizing Illumina's 450k array data biocViews: DNAMethylation, Microarray, TwoChannel, DataImport, Preprocessing, QualityControl Author: Kasper Daniel Hansen, Martin Aryee Maintainer: Kasper Daniel Hansen source.ver: src/contrib/minfi_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/minfi_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/minfi_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/minfi_1.6.0.tgz vignettes: vignettes/minfi/inst/doc/minfi.pdf vignetteTitles: Minfi Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/minfi/inst/doc/minfi.R importsMe: methylumi Package: MinimumDistance Version: 1.4.0 Depends: R (>= 2.14), BiocGenerics (>= 0.3.2), IRanges (>= 1.13.30) Imports: methods, DNAcopy, utils, msm, lattice, BiocGenerics, VanillaICE (>= 1.21.24), ff, Biobase (>= 2.17.8), foreach, oligoClasses (>= 1.21.12), GenomicRanges, matrixStats Suggests: human610quadv1bCrlmm (>= 1.0.3), SNPchip, RUnit Enhances: snow, doSNOW License: Artistic-2.0 MD5sum: cd943b57173e86f719ff85da80569d89 NeedsCompilation: no Title: A package for de novo CNV detection in case-parent trios Description: Analysis of de novo copy number variants in trios from high-dimensional genotyping platforms biocViews: Microarray, SNP, Bioinformatics, CopyNumberVariants Author: Robert B Scharpf and Ingo Ruczinski Maintainer: Robert B Scharpf source.ver: src/contrib/MinimumDistance_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MinimumDistance_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MinimumDistance_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MinimumDistance_1.4.0.tgz vignettes: vignettes/MinimumDistance/inst/doc/MinimumDistance.pdf vignetteTitles: Detection of de novo copy number alterations in case-parent trios hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MinimumDistance/inst/doc/MinimumDistance.R Package: MiPP Version: 1.32.0 Depends: R (>= 2.4) Imports: Biobase, e1071, MASS, stats License: GPL (>= 2) MD5sum: 13141e077d0db66fd243da91afecb68e NeedsCompilation: no Title: Misclassification Penalized Posterior Classification Description: This package finds optimal sets of genes that seperate samples into two or more classes. biocViews: Microarray, Classification Author: HyungJun Cho , Sukwoo Kim , Mat Soukup , and Jae K. Lee Maintainer: Sukwoo Kim URL: http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/ source.ver: src/contrib/MiPP_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MiPP_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MiPP_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MiPP_1.32.0.tgz vignettes: vignettes/MiPP/inst/doc/MiPP.pdf vignetteTitles: MiPP Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MiPP/inst/doc/MiPP.R Package: MiRaGE Version: 1.2.0 Depends: R (>= 2.12.1), Biobase(>= 2.16.0) Imports: AnnotationDbi, BiocGenerics Suggests: seqinr (>= 3.0.3), biomaRt (>= 2.6.0), GenomicFeatures (>= 1.8.1), Biostrings (>= 2.24.1), BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm9, miRNATarget, humanStemCell, IRanges , GenomicRanges (>= 1.8.3), BSgenome, beadarrayExampleData License: GPL MD5sum: 10d5a25979c47f2e6c061bfb9baaeac1 NeedsCompilation: no Title: MiRNA Ranking by Gene Expression Description: The package contains functions for inferece of target gene regulation by miRNA, based on only target gene expression profile. biocViews: Microarray, GeneExpression, RNAseq, RNAseqData, HighThroughputSequencingData, Sequencing, SAGE Author: Y-h. Taguchi Maintainer: Y-h. Taguchi source.ver: src/contrib/MiRaGE_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MiRaGE_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MiRaGE_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MiRaGE_1.2.0.tgz vignettes: vignettes/MiRaGE/inst/doc/MiRaGE.pdf vignetteTitles: How to use MiRaGE Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MiRaGE/inst/doc/MiRaGE.R Package: miRNApath Version: 1.20.0 Depends: methods, R(>= 2.7.0) License: LGPL-2.1 MD5sum: 98b9786370beb2476acc4f3241dc0ce6 NeedsCompilation: no Title: miRNApath: Pathway Enrichment for miRNA Expression Data Description: This package provides pathway enrichment techniques for miRNA expression data. Specifically, the set of methods handles the many-to-many relationship between miRNAs and the multiple genes they are predicted to target (and thus affect.) It also handles the gene-to-pathway relationships separately. Both steps are designed to preserve the additive effects of miRNAs on genes, many miRNAs affecting one gene, one miRNA affecting multiple genes, or many miRNAs affecting many genes. biocViews: Annotation, Pathways, DifferentialExpression, NetworkEnrichment, miRNA Author: James M. Ward with contributions from Yunling Shi, Cindy Richards, John P. Cogswell Maintainer: James M. Ward source.ver: src/contrib/miRNApath_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/miRNApath_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/miRNApath_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/miRNApath_1.20.0.tgz vignettes: vignettes/miRNApath/inst/doc/miRNApath.pdf vignetteTitles: miRNApath: Pathway Enrichment for miRNA Expression Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/miRNApath/inst/doc/miRNApath.R Package: MLInterfaces Version: 1.40.0 Depends: R (>= 2.9), Biobase, MASS, methods, genefilter, rpart, rda, annotate, cluster, sfsmisc Imports: mboost, gdata, pls Suggests: class, e1071, ipred, randomForest, gpls, pamr, rpart, MASS, nnet, ALL, gbm, mlbench, hgu95av2.db, som, RColorBrewer, hu6800.db, lattice, caret (>= 5.07), golubEsets, ada, keggorthology, kernlab, gbm, mboost, sfsmisc, party Enhances: parallel License: LGPL MD5sum: 59a0d936e4a84d3db8b54295b2749b71 NeedsCompilation: no Title: Uniform interfaces to R machine learning procedures for data in Bioconductor containers Description: Uniform interfaces to machine learning code for data in Bioconductor containers biocViews: Bioinformatics, Classification, Clustering Author: Vince Carey , Robert Gentleman, Jess Mar, and contributions from Jason Vertrees and Laurent Gatto Maintainer: V. Carey source.ver: src/contrib/MLInterfaces_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MLInterfaces_1.40.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MLInterfaces_1.40.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MLInterfaces_1.40.0.tgz vignettes: vignettes/MLInterfaces/inst/doc/MLint_devel.pdf, vignettes/MLInterfaces/inst/doc/MLInterfaces.pdf, vignettes/MLInterfaces/inst/doc/MLprac2_2.pdf, vignettes/MLInterfaces/inst/doc/xvalComputerClusters.pdf vignetteTitles: MLInterfaces devel for schema-based MLearn, MLInterfaces Primer, A machine learning tutorial: applications of the Bioconductor MLInterfaces package to expression and ChIP-Seq data, MLInterfaces Computer Cluster hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MLInterfaces/inst/doc/MLint_devel.R, vignettes/MLInterfaces/inst/doc/MLInterfaces.R, vignettes/MLInterfaces/inst/doc/MLprac2_2.R, vignettes/MLInterfaces/inst/doc/xvalComputerClusters.R dependsOnMe: a4Classif, pRoloc suggestsMe: BiocCaseStudies Package: MLP Version: 1.8.1 Depends: AnnotationDbi, affy, plotrix, gplots, gmodels, gdata, gtools Suggests: GO.db, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Cf.eg.db, KEGG.db, annotate, Rgraphviz, GOstats, limma, mouse4302.db, reactome.db License: GPL-3 MD5sum: 292efd1bf9501ae4d6a40a9a4355170d NeedsCompilation: no Title: MLP Description: Mean Log P Analysis biocViews: Genetics Author: Nandini Raghavan, Tobias Verbeke, An De Bondt with contributions by Javier Cabrera, Dhammika Amaratunga, Tine Casneuf and Willem Ligtenberg Maintainer: Tobias Verbeke source.ver: src/contrib/MLP_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/MLP_1.8.1.zip win64.binary.ver: bin/windows64/contrib/2.16/MLP_1.8.1.zip mac.binary.ver: bin/macosx/contrib/2.16/MLP_1.8.1.tgz vignettes: vignettes/MLP/inst/doc/UsingMLP.pdf vignetteTitles: UsingMLP hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MLP/inst/doc/UsingMLP.R suggestsMe: a4 Package: MMDiff Version: 1.0.0 Depends: R (>= 2.14.0),GenomicRanges,parallel,DiffBind,GMD,Rsamtools Imports: GenomicRanges,IRanges Suggests: MMDiffBamSubset License: Artistic-2.0 MD5sum: 4a389510148edffe4b5ef51415cb5939 NeedsCompilation: no Title: Statistical Testing for ChIP-Seq data sets Description: This package detects statistically significant difference between read enrichment profiles in different ChIP-Seq samples. To take advantage of shape differences it uses Kernel methods (Maximum Mean Discrepancy, MMD). biocViews: ChIPseq, MultipleComparisons Author: Gabriele Schweikert Maintainer: Gabriele Schweikert source.ver: src/contrib/MMDiff_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MMDiff_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MMDiff_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MMDiff_1.0.0.tgz vignettes: vignettes/MMDiff/inst/doc/MMDiff.pdf vignetteTitles: Analysing ChIP-Seq data with the "MMDiff" package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MMDiff/inst/doc/MMDiff.R Package: MmPalateMiRNA Version: 1.10.0 Depends: R (>= 2.13.0), methods, Biobase, xtable, limma, statmod, lattice, vsn Imports: limma, lattice, Biobase Suggests: GOstats, graph, Category, org.Mm.eg.db, microRNA, targetscan.Mm.eg.db, RSQLite, DBI, AnnotationDbi, clValid, class, cluster, multtest, RColorBrewer, latticeExtra License: GPL-3 MD5sum: 354ddc019ee5b789f48a068e24aaccd1 NeedsCompilation: no Title: Murine Palate miRNA Expression Analysis Description: R package compendium for the analysis of murine palate miRNA two-color expression data. biocViews: Microarray, TwoChannel, Bioinformatics, QualityControl, Preprocessing, DifferentialExpression, MultipleComparisons, Clustering, GO, Pathways, ReportWriting, SequenceMatching Author: Guy Brock , Partha Mukhopadhyay , Vasyl Pihur , Robert M. Greene , and M. Michele Pisano Maintainer: Guy Brock source.ver: src/contrib/MmPalateMiRNA_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MmPalateMiRNA_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MmPalateMiRNA_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MmPalateMiRNA_1.10.0.tgz vignettes: vignettes/MmPalateMiRNA/inst/doc/MmPalateMiRNA.pdf vignetteTitles: Palate miRNA Analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MmPalateMiRNA/inst/doc/MmPalateMiRNA.R Package: mosaics Version: 1.8.0 Depends: R (>= 2.11.1), methods, graphics, Rcpp Imports: MASS, splines, lattice, IRanges LinkingTo: Rcpp Suggests: mosaicsExample Enhances: parallel License: GPL (>= 2) Archs: i386, x64 MD5sum: ab9ca72202d90896e153cdbc12a8baad NeedsCompilation: yes Title: MOSAiCS (MOdel-based one and two Sample Analysis and Inference for ChIP-Seq) Description: This package provides functions for fitting MOSAiCS, a statistical framework to analyze one-sample or two-sample ChIP-seq data. biocViews: ChIPseq, Sequencing, Transcription, Genetics, Bioinformatics Author: Dongjun Chung, Pei Fen Kuan, Sunduz Keles Maintainer: Dongjun Chung URL: http://groups.google.com/group/mosaics_user_group SystemRequirements: Perl source.ver: src/contrib/mosaics_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/mosaics_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/mosaics_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/mosaics_1.8.0.tgz vignettes: vignettes/mosaics/inst/doc/Figure4a.pdf, vignettes/mosaics/inst/doc/Figure4b.pdf, vignettes/mosaics/inst/doc/Figure5a.pdf, vignettes/mosaics/inst/doc/Figure5b.pdf, vignettes/mosaics/inst/doc/Figure5c.pdf, vignettes/mosaics/inst/doc/Figure5d.pdf, vignettes/mosaics/inst/doc/GOF_matchLow.pdf, vignettes/mosaics/inst/doc/GOF_rMOM.pdf, vignettes/mosaics/inst/doc/mosaics-example.pdf vignetteTitles: Figure4a.pdf, Figure4b.pdf, Figure5a.pdf, Figure5b.pdf, Figure5c.pdf, Figure5d.pdf, GOF_matchLow.pdf, GOF_rMOM.pdf, MOSAiCS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mosaics/inst/doc/mosaics-example.R dependsOnMe: jmosaics Package: MotifDb Version: 1.2.2 Depends: R (>= 2.15.0), methods, IRanges, Biostrings Imports: BiocGenerics, rtracklayer Suggests: RUnit, MotIV, seqLogo License: Artistic-2.0 | file LICENSE License_is_FOSS: no License_restricts_use: yes MD5sum: 610d1d2c42334de8e73b09a1866ea85b NeedsCompilation: no Title: An Annotated Collection of Protein-DNA Binding Sequence Motifs Description: More than 2000 annotated position frequency matrices from five public source, for multiple organisms biocViews: GenomicSequence, MotifAnnotation Author: Paul Shannon Maintainer: Paul Shannon source.ver: src/contrib/MotifDb_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/MotifDb_1.2.2.zip win64.binary.ver: bin/windows64/contrib/2.16/MotifDb_1.2.2.zip mac.binary.ver: bin/macosx/contrib/2.16/MotifDb_1.2.2.tgz vignettes: vignettes/MotifDb/inst/doc/MotifDb.pdf vignetteTitles: MotifDb Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/MotifDb/inst/doc/MotifDb.R suggestsMe: motifStack, PWMEnrich Package: motifRG Version: 1.4.0 Depends: R (>= 2.10) Imports: Biostrings, IRanges, seqLogo, parallel, methods, grid,graphics License: Artistic-2.0 MD5sum: 7a54a3959ffef8fbd77d1347721d53e5 NeedsCompilation: no Title: A package for discriminative motif discovery, designed for high throughput sequencing dataset Description: Tools for discriminative motif discovery using regression methods biocViews: Transcription, MotifDiscovery Author: Zizhen Yao Maintainer: Zizhen Yao source.ver: src/contrib/motifRG_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/motifRG_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/motifRG_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/motifRG_1.4.0.tgz vignettes: vignettes/motifRG/inst/doc/motifRG.pdf vignetteTitles: motifRG: regression-based discriminative motif discovery hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/motifRG/inst/doc/motifRG.R Package: motifStack Version: 1.4.0 Depends: R (>= 2.15.1), methods, grImport, grid, MotIV, ade4 Imports: grImport, grid, XML, ade4 Suggests: RUnit, BiocGenerics, MotifDb, RColorBrewer License: GPL (>= 2) MD5sum: 77e24fa150890ea25558a24f20a111c4 NeedsCompilation: no Title: Plot stacked logos for single or multiple DNA, RNA and amino acid sequence Description: The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motif and amino acid sequence motif. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors. biocViews: SequenceMatching, GenomicsSequence, Visualization Author: Jianhong Ou, Michael Brodsky, Scot Wolfe and Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/motifStack_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/motifStack_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/motifStack_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/motifStack_1.4.0.tgz vignettes: vignettes/motifStack/inst/doc/motifStack.pdf vignetteTitles: motifStack Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/motifStack/inst/doc/motifStack.R Package: MotIV Version: 1.16.0 Depends: R (>= 2.10), BiocGenerics (>= 0.1.0) Imports: graphics, grid, methods, BiocGenerics, IRanges (>= 1.13.5), Biostrings (>= 1.24.0), lattice, rGADEM, stats, utils Suggests: rtracklayer License: GPL-2 Archs: i386, x64 MD5sum: c193e0e91c412acae57a71d39a39029f NeedsCompilation: yes Title: Motif Identification and Validation Description: This package makes use of STAMP for comparing a set of motifs to a given database (e.g. JASPAR). It can also be used to visualize motifs, motif distributions, modules and filter motifs. biocViews: Microarray, ChIPchip, ChIPseq, GenomicSequence, MotifAnnotation Author: Eloi Mercier, Raphael Gottardo Maintainer: Eloi Mercier , Raphael Gottardo source.ver: src/contrib/MotIV_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MotIV_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MotIV_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MotIV_1.16.0.tgz vignettes: vignettes/MotIV/inst/doc/MotIV.pdf vignetteTitles: The MotIV users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MotIV/inst/doc/MotIV.R dependsOnMe: motifStack suggestsMe: MotifDb Package: MSnbase Version: 1.8.0 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.1.3), Biobase (>= 2.15.2), ggplot2, mzR Imports: plyr, IRanges, preprocessCore, vsn, grid, reshape2, stats4, affy, impute Suggests: testthat, zoo, knitr, rols, Rdisop Enhances: foreach, doMC, parallel License: Artistic-2.0 MD5sum: 74a7ea062fa680df4a05d75f8b35520b NeedsCompilation: no Title: MSnbase: Base Functions and Classes for MS-based Proteomics Description: Basic plotting, data manipulation and processing of MS-based Proteomics data biocViews: Infrastructure, Bioinformatics, Proteomics, MassSpectrometry Author: Laurent Gatto with contributions from Guangchuang Yu Maintainer: Laurent Gatto source.ver: src/contrib/MSnbase_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MSnbase_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MSnbase_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MSnbase_1.8.0.tgz vignettes: vignettes/MSnbase/inst/doc/itraqchem.pdf, vignettes/MSnbase/inst/doc/MSnbase-demo.pdf, vignettes/MSnbase/inst/doc/MSnbase-development.pdf, vignettes/MSnbase/inst/doc/MSnbase-io.pdf, vignettes/MSnbase/inst/doc/plotMzDelta-pride12011.pdf vignetteTitles: itraqchem.pdf, Base Functions and Classes for MS-based Proteomics, MSnbase development, MSnbase IO capabilities, plotMzDelta-pride12011.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MSnbase/inst/doc/MSnbase-demo.R, vignettes/MSnbase/inst/doc/MSnbase-development.R, vignettes/MSnbase/inst/doc/MSnbase-io.R dependsOnMe: pRoloc, synapter suggestsMe: isobar Package: Mulcom Version: 1.10.0 Depends: R (>= 2.10), fields, Biobase Imports: graphics, grDevices, stats, methods License: GPL-2 Archs: i386, x64 MD5sum: cb3327c1f353ea0114b7868f0502d696 NeedsCompilation: yes Title: Calculates Mulcom test Description: Identification of differentially expressed genes and false discovery rate (FDR) calculation by Multiple Comparison test biocViews: Statistics, MultipleComparisons, Microarray, DifferentialExpression, GeneExpression Author: Claudio Isella Maintainer: Claudio Isella source.ver: src/contrib/Mulcom_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Mulcom_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Mulcom_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Mulcom_1.10.0.tgz vignettes: vignettes/Mulcom/inst/doc/MulcomVignette.pdf vignetteTitles: Mulcom Manual hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Mulcom/inst/doc/MulcomVignette.R Package: multiscan Version: 1.20.0 Depends: R (>= 2.3.0) Imports: Biobase, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 27c935e954dbcd5b43660c5dc4322ec6 NeedsCompilation: yes Title: R package for combining multiple scans Description: Estimates gene expressions from several laser scans of the same microarray biocViews: Microarray, Preprocessing Author: Mizanur Khondoker , Chris Glasbey, Bruce Worton. Maintainer: Mizanur Khondoker source.ver: src/contrib/multiscan_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/multiscan_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/multiscan_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/multiscan_1.20.0.tgz vignettes: vignettes/multiscan/inst/doc/multiscan.pdf vignetteTitles: An R Package for Estimating Gene Expressions using Multiple Scans hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/multiscan/inst/doc/multiscan.R Package: multtest Version: 2.16.0 Depends: R (>= 2.10), methods, Biobase Imports: survival, MASS, stats4 Suggests: snow License: LGPL Archs: i386, x64 MD5sum: 2db3b625b5eac733591c4adeabd9b5bb NeedsCompilation: yes Title: Resampling-based multiple hypothesis testing Description: Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments. biocViews: Microarray, DifferentialExpression, MultipleComparisons Author: Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra Taylor, Sandrine Dudoit Maintainer: Katherine S. Pollard source.ver: src/contrib/multtest_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/multtest_2.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/multtest_2.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/multtest_2.16.0.tgz vignettes: vignettes/multtest/inst/doc/MTPALL.pdf, vignettes/multtest/inst/doc/MTP.pdf, vignettes/multtest/inst/doc/multtest.pdf vignetteTitles: MTPALL.pdf, MTP.pdf, multtest.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4Base, aCGH, BicARE, ChIPpeakAnno, iPAC, KCsmart, LMGene, PREDA, REDseq, SAGx, siggenes, webbioc importsMe: ABarray, aCGH, adSplit, anota, ChIPpeakAnno, GeneSelector, globaltest, IsoGeneGUI, OCplus, phyloseq, REDseq, RTopper, synapter, webbioc suggestsMe: annaffy, BiocCaseStudies, ecolitk, factDesign, GeneSelector, GOstats, GSEAlm, maigesPack, MmPalateMiRNA, oneChannelGUI, pcot2, topGO, xcms Package: MVCClass Version: 1.34.0 Depends: R (>= 2.1.0), methods License: LGPL MD5sum: aabba378f6941fbb15691643fa3fb653 NeedsCompilation: no Title: Model-View-Controller (MVC) Classes Description: Creates classes used in model-view-controller (MVC) design biocViews: Visualization, Infrastructure, GraphsAndNetworks Author: Elizabeth Whalen Maintainer: Elizabeth Whalen source.ver: src/contrib/MVCClass_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/MVCClass_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/MVCClass_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/MVCClass_1.34.0.tgz vignettes: vignettes/MVCClass/inst/doc/MVCClass.pdf vignetteTitles: MVCClass hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MVCClass/inst/doc/MVCClass.R dependsOnMe: BioMVCClass Package: mzR Version: 1.6.3 Depends: Rcpp (>= 0.10.1), methods, utils Imports: Biobase LinkingTo: Rcpp Suggests: msdata (>= 0.1.9), RUnit, faahKO License: Artistic-2.0 Archs: i386, x64 MD5sum: c2bf4be3c3a46e4ea7056406d3e7d429 NeedsCompilation: yes Title: parser for netCDF, mzXML, mzData and mzML files (mass spectrometry data) Description: mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a wrapper for the ISB random access parser for mass spectrometry mzXML, mzData and mzML files. The package contains the original code written by the ISB, and a subset of the proteowizard library for mzML. The netCDF reading code has previously been used in XCMS. biocViews: Infrastructure, Bioinformatics, DataImport, Proteomics, Metabolomics, MassSpectrometry Author: Bernd Fischer, Steffen Neumann, Laurent Gatto Maintainer: Bernd Fischer , Steffen Neumann , Laurent Gatto SystemRequirements: GNU make, NetCDF, zlib source.ver: src/contrib/mzR_1.6.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/mzR_1.6.3.zip win64.binary.ver: bin/windows64/contrib/2.16/mzR_1.6.3.zip mac.binary.ver: bin/macosx/contrib/2.16/mzR_1.6.3.tgz vignettes: vignettes/mzR/inst/doc/mzR.pdf vignetteTitles: mzR,, Ramp,, mzXML,, mzData,, mzML hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mzR/inst/doc/mzR.R dependsOnMe: MSnbase, TargetSearch, xcms Package: NarrowPeaks Version: 1.4.0 Depends: R (>= 2.10.0), splines Imports: GenomicRanges, IRanges, fda, CSAR Suggests: rtracklayer, GenomicRanges, CSAR License: Artistic-2.0 Archs: i386, x64 MD5sum: 9c028f1a37e9b4ed015bb8f3c954549d NeedsCompilation: yes Title: Analysis of Variation in ChIP-seq using Functional PCA Statistics Description: The double aim of the package is to apply a functional version of principal component analysis (FPCA) to: (1) Process data in wiggle track format (WIG) commonly produced by ChIP-seq peak finders by applying FPCA over a set of selected candidate enriched regions. This is done in order to shorten the genomic locations accounting for a given proportion of variation among the enrichment-score profiles. The function 'narrowpeaks' allows the user to discriminate between binding regions in close proximity to each other and to narrow down the length of the putative transcription factor binding sites while preserving the information present in the variability of the dataset and capturing major sources of variation. (2) Analyze differential variation when multiple ChIP-seq samples need to compared. The function 'narrowpeaksDiff' quantifies differences between the tag-enrichment, and uses non-parametric tests on the FPC scores for testing differences between conditions. biocViews: Visualization, ChIPseq, Transcription, Genetics Author: Pedro Madrigal , with contributions from Pawel Krajewski Maintainer: Pedro Madrigal source.ver: src/contrib/NarrowPeaks_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/NarrowPeaks_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/NarrowPeaks_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/NarrowPeaks_1.4.0.tgz vignettes: vignettes/NarrowPeaks/inst/doc/NarrowPeaksDiff.pdf, vignettes/NarrowPeaks/inst/doc/NarrowPeaks.pdf vignetteTitles: NarrowPeaks Vignette II. Inter-sample variability: Analysis of variation in differential binding across ChIP-seq samples., NarrowPeaks Vignette I. Intra-sample variability: Splitting and narrowing down ChIP-seq peaks in a single experiment. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NarrowPeaks/inst/doc/NarrowPeaksDiff.R, vignettes/NarrowPeaks/inst/doc/NarrowPeaks.R Package: ncdfFlow Version: 1.6.1 Depends: R (>= 2.14.0), flowCore (>= 1.25.9) Imports: Biobase,flowCore,flowViz (>= 1.23.1),methods License: Artistic-2.0 MD5sum: dacb191ee9bdb4eb5e03455d36c592d8 NeedsCompilation: yes Title: ncdfFlow: A package that provides ncdf based storage for flow cytometry data. Description: Provides netCDF storage based methods and functions for manipulation of flow cytometry data. biocViews: FlowCytometry Author: Mike Jiang,Greg Finak,N. Gopalakrishnan Maintainer: M. Jiang SystemRequirements: netcdf 4.0.1, hdf5 source.ver: src/contrib/ncdfFlow_1.6.1.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/ncdfFlow_1.6.1.tgz vignettes: vignettes/ncdfFlow/inst/doc/ncdfFlow.pdf vignetteTitles: Basic Functions for Flow Cytometry Data hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ncdfFlow/inst/doc/ncdfFlow.R Package: NCIgraph Version: 1.8.0 Depends: graph, R (>= 2.10.0) Imports: graph, KEGGgraph, methods, RBGL, RCytoscape, R.methodsS3 Suggests: Rgraphviz Enhances: DEGraph License: GPL-3 MD5sum: 22385aac6213c1d4e439b8b54cc0eca9 NeedsCompilation: no Title: Pathways from the NCI Pathways Database Description: Provides various methods to load the pathways from the NCI Pathways Database in R graph objects and to re-format them. biocViews: Pathways, GraphsAndNetworks Author: Laurent Jacob Maintainer: Laurent Jacob source.ver: src/contrib/NCIgraph_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/NCIgraph_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/NCIgraph_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/NCIgraph_1.8.0.tgz vignettes: vignettes/NCIgraph/inst/doc/NCIgraph.pdf vignetteTitles: NCIgraph: networks from the NCI pathway integrated database as graphNEL objects. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NCIgraph/inst/doc/NCIgraph.R importsMe: DEGraph suggestsMe: DEGraph Package: nem Version: 2.36.0 Depends: R (>= 2.0), e1071 (>= 1.5), graph (>= 1.24), plotrix, limma, cluster (>= 1.11), statmod, Hmisc, Rgraphviz Imports: boot, e1071, graph, graphics, grDevices, methods, RBGL (>= 1.8.1), RColorBrewer, stats, utils, Rgraphviz Suggests: Biobase (>= 1.10) Enhances: doMC, Rglpk License: GPL (>= 2) Archs: i386, x64 MD5sum: 5d6cea889dfd47b9c32fe816ef2ff925 NeedsCompilation: yes Title: (Dynamic) Nested Effects Models and Deterministic Effects Propagation Networks to reconstruct phenotypic hierarchies Description: The package 'nem' allows to reconstruct features of pathways from the nested structure of perturbation effects. It takes as input (1.) a set of pathway components, which were perturbed, and (2.) phenotypic readout of these perturbations (e.g. gene expression, protein expression). The output is a directed graph representing the phenotypic hierarchy. biocViews: Microarray, Bioinformatics, GraphsAndNetworks, Pathways Author: Holger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth Maintainer: Holger Froehlich URL: http://www.bioconductor.org source.ver: src/contrib/nem_2.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/nem_2.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/nem_2.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/nem_2.36.0.tgz vignettes: vignettes/nem/inst/doc/markowetz-thesis-2006.pdf, vignettes/nem/inst/doc/nem.pdf vignetteTitles: markowetz-thesis-2006.pdf, Nested Effects Models - An example in Drosophila immune response hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nem/inst/doc/nem.R dependsOnMe: lpNet Package: netresponse Version: 1.12.0 Depends: R (>= 2.15.1), dmt, igraph0, infotheo, ggplot2, graph, mclust, methods, minet, parallel, qvalue, RColorBrewer, reshape, Rgraphviz License: GPL (>=2) Archs: i386, x64 MD5sum: 81a51165ec80508eb4c67a339a303d48 NeedsCompilation: yes Title: NetResponse: functional network analysis Description: Algorithms for functional network analysis. Includes an implementation of a variational Dirichlet process Gaussian mixture model for nonparametric mixture modeling. biocViews: CellBiology, Clustering, GeneExpression, Genetics, NetworkAnalysis, GraphsAndNetworks, DifferentialExpression, Microarray, Transcription Author: Leo Lahti, Olli-Pekka Huovilainen, Antonio Gusmao and Juuso Parkkinen Maintainer: Leo Lahti URL: http://netpro.r-forge.r-project.org/ source.ver: src/contrib/netresponse_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/netresponse_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/netresponse_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/netresponse_1.12.0.tgz vignettes: vignettes/netresponse/inst/doc/netresponse.pdf vignetteTitles: netresponse hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/netresponse/inst/doc/netresponse.R Package: networkBMA Version: 1.2.0 Depends: R (>= 2.15.0), stats, utils, BMA License: GPL (>= 2) MD5sum: fd92a42960d03865a672c3b6051dab02 NeedsCompilation: no Title: Regression-based network inference using Bayesian Model Averaging Description: An extension of Bayesian Model Averaging (BMA) for network construction using time series gene expression data. Includes assessment functions and sample test data. biocViews: GraphsAndNetworks, NetworkInference Author: Chris Fraley, Ka Yee Yeung, Adrian Raftery (with contributions from Kenneth Lo and Chad Young) Maintainer: Chris Fraley source.ver: src/contrib/networkBMA_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/networkBMA_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/networkBMA_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/networkBMA_1.2.0.tgz vignettes: vignettes/networkBMA/inst/doc/networkBMA.pdf, vignettes/networkBMA/inst/doc/prc.pdf, vignettes/networkBMA/inst/doc/roc.pdf vignetteTitles: networkBMA, prc.pdf, roc.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/networkBMA/inst/doc/networkBMA.R Package: nnNorm Version: 2.24.0 Depends: R(>= 2.2.0), marray Imports: graphics, grDevices, marray, methods, nnet, stats License: LGPL MD5sum: 89f1e75fbe519069d08f1dc0d4697213 NeedsCompilation: no Title: Spatial and intensity based normalization of cDNA microarray data based on robust neural nets Description: This package allows to detect and correct for spatial and intensity biases with two-channel microarray data. The normalization method implemented in this package is based on robust neural networks fitting. biocViews: Microarray, TwoChannel, Preprocessing Author: Adi Laurentiu Tarca Maintainer: Adi Laurentiu Tarca URL: http://bioinformaticsprb.med.wayne.edu/tarca/ source.ver: src/contrib/nnNorm_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/nnNorm_2.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/nnNorm_2.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/nnNorm_2.24.0.tgz vignettes: vignettes/nnNorm/inst/doc/nnNormGuide.pdf, vignettes/nnNorm/inst/doc/nnNorm.pdf vignetteTitles: nnNormGuide.pdf, nnNorm Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nnNorm/inst/doc/nnNorm.R Package: NOISeq Version: 2.0.0 Depends: R (>= 2.13.0), methods, Biobase (>= 2.13.11), splines (>= 3.0.1) License: Artistic-2.0 MD5sum: c1530711d5d4af35fbcec5b036415795 NeedsCompilation: no Title: Exploratory analysis and differential expression for RNA-seq data Description: Analysis of RNA-seq expression data or other similar kind of data. Exploratory plots to evualuate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. Differential expression between two experimental conditions with no parametric assumptions. biocViews: Bioinformatics, RNAseq, DifferentialExpression, Visualization, HighThroughputSequencing Author: Sonia Tarazona, Pedro Furio-Tari, Alberto Ferrer and Ana Conesa Maintainer: Sonia Tarazona source.ver: src/contrib/NOISeq_2.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/NOISeq_2.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/NOISeq_2.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/NOISeq_2.0.0.tgz vignettes: vignettes/NOISeq/inst/doc/NOISeq.pdf vignetteTitles: NOISeq User's Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NOISeq/inst/doc/NOISeq.R Package: NormqPCR Version: 1.6.0 Depends: R(>= 2.14.0), stats, RColorBrewer, Biobase, methods, ReadqPCR, qpcR Imports: ReadqPCR License: LGPL-3 MD5sum: 014d87f0d761c1070e3c7f16776540f0 NeedsCompilation: no Title: Functions for normalisation of RT-qPCR data Description: Functions for the selection of optimal reference genes and the normalisation of real-time quantitative PCR data. biocViews: MicrotitrePlateAssay, GeneExpression, qPCR Author: Matthias Kohl, James Perkins, Nor Izayu Abdul Rahman Maintainer: James Perkins URL: www.bioconductor.org/packages/release/bioc/html/NormqPCR.html source.ver: src/contrib/NormqPCR_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/NormqPCR_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/NormqPCR_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/NormqPCR_1.6.0.tgz vignettes: vignettes/NormqPCR/inst/doc/NormqPCR.pdf vignetteTitles: NormqPCR: Functions for normalisation of RT-qPCR data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NormqPCR/inst/doc/NormqPCR.R Package: NTW Version: 1.10.0 Depends: R (>= 2.3.0) Imports: mvtnorm, stats, utils License: GPL-2 MD5sum: 6b9ff0a0055bc15d27f825f7afdaa9d1 NeedsCompilation: no Title: Predict gene network using an Ordinary Differential Equation (ODE) based method Description: This package predicts the gene-gene interaction network and identifies the direct transcriptional targets of the perturbation using an ODE (Ordinary Differential Equation) based method. biocViews: Preprocessing Author: Wei Xiao, Yin Jin, Darong Lai, Xinyi Yang, Yuanhua Liu, Christine Nardini Maintainer: Yuanhua Liu source.ver: src/contrib/NTW_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/NTW_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/NTW_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/NTW_1.10.0.tgz vignettes: vignettes/NTW/inst/doc/NTW.pdf vignetteTitles: NTW vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NTW/inst/doc/NTW.R Package: nucleR Version: 1.8.0 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.5), Biobase (>= 2.15.1), ShortRead, parallel Imports: methods, BiocGenerics, IRanges, Biobase, ShortRead, GenomicRanges, stats Enhances: htSeqTools License: LGPL (>= 3) MD5sum: 80c78d29bb5a9b9ef4bc0a95f2e0ec20 NeedsCompilation: no Title: Nucleosome positioning package for R Description: Nucleosome positioning for Tiling Arrays and Next Generation Sequencing Experiments biocViews: ChIPseq, Microarray, Sequencing, Genetics, HighThroughputSequencing Author: Oscar Flores, David Rossell Maintainer: Oscar Flores source.ver: src/contrib/nucleR_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/nucleR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/nucleR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/nucleR_1.8.0.tgz vignettes: vignettes/nucleR/inst/doc/nucleR.pdf vignetteTitles: Quick analysis of nucleosome positioning experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nucleR/inst/doc/nucleR.R Package: nudge Version: 1.26.0 Imports: stats License: GPL-2 MD5sum: 132a73ad35fb0aaaf0423a05a8e08bd8 NeedsCompilation: no Title: Normal Uniform Differential Gene Expression detection Description: Package for normalizing microarray data in single and multiple replicate experiments and fitting a normal-uniform mixture to detect differentially expressed genes in the cases where the two samples are being compared directly or indirectly (via a common reference sample) biocViews: Microarray, TwoChannel, DifferentialExpression Author: N. Dean and A. E. Raftery Maintainer: N. Dean source.ver: src/contrib/nudge_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/nudge_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/nudge_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/nudge_1.26.0.tgz vignettes: vignettes/nudge/inst/doc/nudge.vignette.pdf, vignettes/nudge/inst/doc/nvignplot1.pdf, vignettes/nudge/inst/doc/nvignplot2.pdf, vignettes/nudge/inst/doc/nvignplot3.pdf, vignettes/nudge/inst/doc/nvignplot4.pdf vignetteTitles: nudge Overview, nvignplot1.pdf, nvignplot2.pdf, nvignplot3.pdf, nvignplot4.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nudge/inst/doc/nudge.vignette.R Package: NuPoP Version: 1.10.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: aacfd6eba8f038fe87efa38361526382 NeedsCompilation: yes Title: An R package for nucleosome positioning prediction Description: NuPoP is an R package for Nucleosome Positioning Prediction.This package is built upon a duration hidden Markov model proposed in Xi et al, 2010; Wang et al, 2008. The core of the package was written in Fotran. In addition to the R package, a stand-alone Fortran software tool is also available at http://nucleosome.stats.northwestern.edu. biocViews: Genetics,Visualization,Classification Author: Ji-Ping Wang ; Liqun Xi Maintainer: Ji-Ping Wang source.ver: src/contrib/NuPoP_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/NuPoP_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/NuPoP_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/NuPoP_1.10.0.tgz vignettes: vignettes/NuPoP/inst/doc/NuPoP-intro.pdf, vignettes/NuPoP/inst/doc/NuPoP-manual.pdf vignetteTitles: An R package for Nucleosome positioning prediction, NuPoP-manual.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NuPoP/inst/doc/NuPoP-intro.R Package: occugene Version: 1.20.0 Depends: R (>= 2.0.0) License: GPL (>= 2) MD5sum: b9bd12ce60a74d31b553c8695a4c655f NeedsCompilation: no Title: Functions for Multinomial Occupancy Distribution Description: Statistical tools for building random mutagenesis libraries for prokaryotes. The package has functions for handling the occupancy distribution for a multinomial and for estimating the number of essential genes in random transposon mutagenesis libraries. biocViews: Bioinformatics,Annotation,Pathways Author: Oliver Will Maintainer: Oliver Will source.ver: src/contrib/occugene_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/occugene_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/occugene_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/occugene_1.20.0.tgz vignettes: vignettes/occugene/inst/doc/occugene.pdf vignetteTitles: occugene hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/occugene/inst/doc/occugene.R Package: OCplus Version: 1.34.0 Depends: R (>= 2.1.0), akima Imports: multtest (>= 1.7.3), graphics, grDevices, stats License: LGPL MD5sum: 850402580cbb961aa64ef3c94b4625c8 NeedsCompilation: no Title: Operating characteristics plus sample size and local fdr for microarray experiments Description: This package allows to characterize the operating characteristics of a microarray experiment, i.e. the trade-off between false discovery rate and the power to detect truly regulated genes. The package includes tools both for planned experiments (for sample size assessment) and for already collected data (identification of differentially expressed genes). biocViews: Microarray, Bioinformatics, DifferentialExpression, MultipleComparisons Author: Yudi Pawitan and Alexander Ploner Maintainer: Alexander Ploner source.ver: src/contrib/OCplus_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OCplus_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OCplus_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OCplus_1.34.0.tgz vignettes: vignettes/OCplus/inst/doc/OCplus.pdf vignetteTitles: OCplus Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OCplus/inst/doc/OCplus.R Package: oligo Version: 1.24.2 Depends: R (>= 2.15.0), BiocGenerics (>= 0.3.2), oligoClasses (>= 1.19.43), Biobase (>= 2.17.8) Imports: affyio (>= 1.25.0), affxparser (>= 1.29.11), Biostrings (>= 2.25.12), BiocGenerics (>= 0.3.2), DBI (>= 0.2-5), ff, graphics, methods, preprocessCore (>= 1.19.0), splines, stats, stats4, utils, zlibbioc LinkingTo: preprocessCore Suggests: hapmap100kxba, pd.mapping50k.xba240, pd.huex.1.0.st.v2, pd.hg18.60mer.expr, pd.hugene.1.0.st.v1, maqcExpression4plex, genefilter, limma, RColorBrewer, oligoData, RUnit Enhances: ff, doMC, doMPI License: LGPL (>= 2) Archs: i386, x64 MD5sum: 323d15f1fe06ce6a7ddd674f2abbe3ae NeedsCompilation: yes Title: Preprocessing tools for oligonucleotide arrays. Description: A package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files). biocViews: Microarray, OneChannel, TwoChannel, Preprocessing, SNP, DifferentialExpression, ExonArray, GeneExpression, Bioinformatics, DataImport Author: Benilton Carvalho and Rafael Irizarry. Contributors: Ben Bolstad, Vincent Carey, Wolfgang Huber, Harris Jaffee, Jim MacDonald, Matt Settles Maintainer: Benilton Carvalho source.ver: src/contrib/oligo_1.24.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/oligo_1.24.2.zip win64.binary.ver: bin/windows64/contrib/2.16/oligo_1.24.2.zip mac.binary.ver: bin/macosx/contrib/2.16/oligo_1.24.2.tgz vignettes: vignettes/oligo/inst/doc/primer.pdf vignetteTitles: oligo - Primer hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/oligo/inst/doc/primer.R dependsOnMe: ITALICS, pdInfoBuilder, SCAN.UPC, waveTiling importsMe: charm, cn.farms, frma, ITALICS suggestsMe: BiocGenerics, fastseg, frmaTools Package: oligoClasses Version: 1.22.0 Depends: R (>= 2.14), BiocGenerics (>= 0.3.2) Imports: BiocGenerics, Biobase (>= 2.17.8), methods, graphics, IRanges (>= 1.13.30), GenomicRanges, Biostrings (>= 2.23.6), affyio (>= 1.23.2), ff, foreach, BiocInstaller, utils Suggests: RSQLite, hapmapsnp5, hapmapsnp6, pd.genomewidesnp.6, pd.genomewidesnp.5, pd.mapping50k.hind240, pd.mapping50k.xba240, pd.mapping250k.sty, pd.mapping250k.nsp, genomewidesnp6Crlmm (>= 1.0.7), genomewidesnp5Crlmm (>= 1.0.6), crlmm, SNPchip, VanillaICE, RUnit, human370v1cCrlmm Enhances: doMC, doMPI, doSNOW, doParallel, doRedis License: GPL (>= 2) MD5sum: fd4756c6c903c54c35fec35b5ea30029 NeedsCompilation: no Title: Classes for high-throughput arrays supported by oligo and crlmm Description: This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages. biocViews: Infrastructure Author: Benilton Carvalho and Robert Scharpf Maintainer: Benilton Carvalho and Robert Scharpf source.ver: src/contrib/oligoClasses_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/oligoClasses_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/oligoClasses_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/oligoClasses_1.22.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: cn.farms, crlmm, mBPCR, oligo, waveTiling importsMe: affycoretools, frma, ITALICS, MinimumDistance, SNPchip, VanillaICE suggestsMe: BiocGenerics Package: OLIN Version: 1.38.0 Depends: R (>= 2.10), methods, locfit, marray Imports: graphics, grDevices, limma, marray, methods, stats Suggests: convert License: GPL-2 MD5sum: 2dbe2c8c35e8bf0ca771f425c47600b7 NeedsCompilation: no Title: Optimized local intensity-dependent normalisation of two-color microarrays Description: Functions for normalisation of two-color microarrays by optimised local regression and for detection of artefacts in microarray data biocViews: Microarray, TwoChannel, QualityControl, Preprocessing, Visualization Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/OLIN/index.html source.ver: src/contrib/OLIN_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OLIN_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OLIN_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OLIN_1.38.0.tgz vignettes: vignettes/OLIN/inst/doc/OLIN.pdf vignetteTitles: Introduction to OLIN hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OLIN/inst/doc/OLIN.R dependsOnMe: OLINgui importsMe: OLINgui suggestsMe: maigesPack Package: OLINgui Version: 1.34.0 Depends: R (>= 2.0.0), OLIN (>= 1.4.0) Imports: graphics, marray, OLIN, tcltk, tkWidgets, widgetTools License: GPL-2 MD5sum: fa129133330afdae5eb8d42b3d66e8fa NeedsCompilation: no Title: Graphical user interface for OLIN Description: Graphical user interface for the OLIN package biocViews: Microarray, TwoChannel, QualityControl, Preprocessing, Visualization Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/OLIN/index.html source.ver: src/contrib/OLINgui_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OLINgui_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OLINgui_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OLINgui_1.34.0.tgz vignettes: vignettes/OLINgui/inst/doc/OLINgui.pdf, vignettes/OLINgui/inst/doc/OLINguiScreenshot.pdf vignetteTitles: Introduction to OLINgui, OLINguiScreenshot.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OLINgui/inst/doc/OLINgui.R Package: oneChannelGUI Version: 1.26.0 Depends: Biobase, affylmGUI, tkWidgets, IRanges, Rsamtools, Biostrings, siggenes, chimera Suggests: annotate, genefilter, maSigPro, pamr, pdmclass, ChIPpeakAnno, chipseq, BSgenome, Rgraphviz, affy ,annaffy, affyPLM, multtest, ssize, sizepower, RankProd, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, edgeR, metaArray, MergeMaid, biomaRt, GenomeGraphs,AffyCompatible, rtracklayer, Genominator, EDASeq, limma, DESeq, DEXSeq, goseq, hugene10sttranscriptcluster.db, mogene10sttranscriptcluster.db, ragene10sttranscriptcluster.db, GOstats, AnnotationDbi, preprocessCore, baySeq, HuExExonProbesetLocation, MoExExonProbesetLocation, RaExExonProbesetLocation, snow, RmiR, RmiR.Hs.miRNA, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm9, BSgenome.Rnorvegicus.UCSC.rn4, R.utils, cummeRbund License: Artistic-2.0 MD5sum: c052802edb0760ccca1c7da69f8b841d NeedsCompilation: no Title: A graphical interface designed to facilitate analysis of microarrays and miRNA/RNA-seq data on laptops. Description: This package was developed to simplify the use of Bioconductor tools for beginners having limited or no experience in writing R code. This library provides a graphical interface for microarray gene and exon level analysis as well as miRNA/mRNA-seq data analysis. biocViews: HighThroughputSequencing, RNAseq, Microarray, OneChannel, DataImport, QualityControl, Preprocessing, Statistics, DifferentialExpression, GUI, MultipleComparisons Author: Raffale A Calogero, Bioinformatics and Genomics Unit, Molecular Biotechnology Center, Torino (Italy) Maintainer: Raffaele A Calogero URL: http://www.bioinformatica.unito.it/oneChannelGUI/ source.ver: src/contrib/oneChannelGUI_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/oneChannelGUI_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/oneChannelGUI_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/oneChannelGUI_1.26.0.tgz vignettes: vignettes/oneChannelGUI/inst/doc/Exon-level.analysis.pdf, vignettes/oneChannelGUI/inst/doc/fignew42.pdf, vignettes/oneChannelGUI/inst/doc/gene-level.analysis.pdf, vignettes/oneChannelGUI/inst/doc/install.pdf, vignettes/oneChannelGUI/inst/doc/RNAseq.pdf, vignettes/oneChannelGUI/inst/doc/standAloneFunctions.pdf vignetteTitles: oneChannelGUI microarray exon-level data analysis overview, fignew42.pdf, oneChannelGUI microarray gene-level data analysis overview, oneChannelGUI Installation, oneChannelGUI miRNA and RNA-seq data analysis overview, oneChannelGUI Stand Alone Functions hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/oneChannelGUI/inst/doc/Exon-level.analysis.R, vignettes/oneChannelGUI/inst/doc/gene-level.analysis.R, vignettes/oneChannelGUI/inst/doc/install.R, vignettes/oneChannelGUI/inst/doc/RNAseq.R, vignettes/oneChannelGUI/inst/doc/standAloneFunctions.R Package: ontoCAT Version: 1.12.0 Depends: rJava, methods License: Apache License 2.0 MD5sum: 26cbcdd796e98fc4155cd31c5d030def NeedsCompilation: no Title: Ontology traversal and search Description: The ontoCAT R package provides a simple interface to ontologies described in widely used standard formats, stored locally in the filesystem or accessible online. The full version of ontoCAT R package also supports searching for ontology terms across multiple ontologies and in major ontology repositories, as well as a number of advanced ontology navigation functions: www.ontocat.org/wiki/r biocViews: Classification, DataRepresentation Author: Natalja Kurbatova, Tomasz Adamusiak, Pavel Kurnosov, Morris Swertz, Misha Kapushevsky Maintainer: Natalja Kurbatova source.ver: src/contrib/ontoCAT_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ontoCAT_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ontoCAT_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ontoCAT_1.12.0.tgz vignettes: vignettes/ontoCAT/inst/doc/ontoCAT.pdf vignetteTitles: ontoCAT package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ontoCAT/inst/doc/ontoCAT.R Package: OrderedList Version: 1.32.0 Depends: R (>= 2.1.0), Biobase (>= 1.5.12), twilight (>= 1.9.2), methods Imports: Biobase, graphics, methods, stats, twilight License: GPL (>= 2) MD5sum: c305318003d64e59f320261ad976d09a NeedsCompilation: no Title: Similarities of Ordered Gene Lists Description: Detection of similarities between ordered lists of genes. Thereby, either simple lists can be compared or gene expression data can be used to deduce the lists. Significance of similarities is evaluated by shuffling lists or by resampling in microarray data, respectively. biocViews: Microarray, DifferentialExpression, MultipleComparisons Author: Xinan Yang, Stefanie Scheid, Claudio Lottaz Maintainer: Claudio Lottaz URL: http://compdiag.molgen.mpg.de/software/index.shtml source.ver: src/contrib/OrderedList_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OrderedList_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OrderedList_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OrderedList_1.32.0.tgz vignettes: vignettes/OrderedList/inst/doc/bcb_logo.pdf, vignettes/OrderedList/inst/doc/tr_2006_01.pdf vignetteTitles: bcb_logo.pdf, Similarities of Ordered Gene Lists hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OrderedList/inst/doc/tr_2006_01.R Package: OrganismDbi Version: 1.2.0 Depends: R (>= 2.14.0), methods, AnnotationDbi (>= 1.16.10), GenomicFeatures Imports: BiocGenerics, graph, RBGL, AnnotationDbi Suggests: Homo.sapiens, Rattus.norvegicus, RUnit License: Artistic-2.0 MD5sum: 4c6fa1dadd859ca017476abae4a237c3 NeedsCompilation: no Title: Software to enable the smooth interfacing of different database packages. Description: The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods. biocViews: Annotation, Infrastructure Author: Marc Carlson, Herve Pages, Martin Morgan, Valerie Obenchain Maintainer: Biocore Data Team source.ver: src/contrib/OrganismDbi_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OrganismDbi_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OrganismDbi_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OrganismDbi_1.2.0.tgz vignettes: vignettes/OrganismDbi/inst/doc/OrganismDbi.pdf vignetteTitles: OrganismDbi: A meta framework for Annotation Packages hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OrganismDbi/inst/doc/OrganismDbi.R Package: OSAT Version: 1.8.1 Depends: methods,stats Suggests: xtable, Biobase License: Artistic-2.0 MD5sum: 58c1124d8e32e9fa79b5a9f31a1b8685 NeedsCompilation: no Title: OSAT: Optimal Sample Assignment Tool Description: A sizable genomics study such as microarray often involves the use of multiple batches (groups) of experiment due to practical complication. To minimize batch effects, a careful experiment design should ensure the even distribution of biological groups and confounding factors across batches. OSAT (Optimal Sample Assignment Tool) is developed to facilitate the allocation of collected samples to different batches. With minimum steps, it produces setup that optimizes the even distribution of samples in groups of biological interest into different batches, reducing the confounding or correlation between batches and the biological variables of interest. It can also optimize the even distribution of confounding factors across batches. Our tool can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideal balanced RCBD. OSAT provides a number of predefined layout for some of the most commonly used genomics platform. Related paper can be find at http://www.biomedcentral.com/1471-2164/13/689 . biocViews: Bioinformatics, DataRepresentation, Visualization, Design, QualityControl Author: Li Yan Maintainer: Li Yan URL: http://www.biomedcentral.com/1471-2164/13/689 source.ver: src/contrib/OSAT_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/OSAT_1.8.1.zip win64.binary.ver: bin/windows64/contrib/2.16/OSAT_1.8.1.zip mac.binary.ver: bin/macosx/contrib/2.16/OSAT_1.8.1.tgz vignettes: vignettes/OSAT/inst/doc/gSetupBlock.pdf, vignettes/OSAT/inst/doc/gSetupOptimal.pdf, vignettes/OSAT/inst/doc/Meth450_Tracking_Sheet_onepage.pdf, vignettes/OSAT/inst/doc/OSAT.pdf, vignettes/OSAT/inst/doc/paired.pdf, vignettes/OSAT/inst/doc/random.pdf vignetteTitles: gSetupBlock.pdf, gSetupOptimal.pdf, Meth450_Tracking_Sheet_onepage.pdf, An introduction to OSAT, paired.pdf, random.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OSAT/inst/doc/OSAT.R Package: OTUbase Version: 1.10.0 Depends: R (>= 2.9.0), methods, ShortRead (>= 1.4.0), Biobase, vegan Imports: Biostrings, ShortRead, IRanges License: Artistic-2.0 MD5sum: c143811cd6928efc926c14196d7a57db NeedsCompilation: no Title: Provides structure and functions for the analysis of OTU data Description: Provides a platform for Operational Taxonomic Unit based analysis biocViews: Bioinformatics, HighThroughputSequencingData, DataImport Author: Daniel Beck, Matt Settles, and James A. Foster Maintainer: Daniel Beck source.ver: src/contrib/OTUbase_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OTUbase_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OTUbase_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OTUbase_1.10.0.tgz vignettes: vignettes/OTUbase/inst/doc/Introduction_to_OTUbase.pdf vignetteTitles: An introduction to OTUbase hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OTUbase/inst/doc/Introduction_to_OTUbase.R dependsOnMe: mcaGUI Package: OutlierD Version: 1.24.0 Depends: R (>= 2.3.0), Biobase, quantreg License: GPL (>= 2) MD5sum: 336e4550d7e0fbc6db5710b4f7f1eecc NeedsCompilation: no Title: Outlier detection using quantile regression on the M-A scatterplots of high-throughput data Description: This package detects outliers using quantile regression on the M-A scatterplots of high-throughput data. biocViews: Microarray, Bioinformatics Author: HyungJun Cho Maintainer: Sukwoo Kim URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/OutlierD_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/OutlierD_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/OutlierD_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/OutlierD_1.24.0.tgz vignettes: vignettes/OutlierD/inst/doc/OutlierD.pdf vignetteTitles: Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OutlierD/inst/doc/OutlierD.R Package: PADOG Version: 1.2.0 Depends: R (>= 2.14.0), KEGGdzPathwaysGEO, graphics, limma, AnnotationDbi, Biobase, methods, nlme, GSA,KEGG.db Imports: graphics, limma, hgu133plus2.db, hgu133a.db, KEGG.db, AnnotationDbi, Biobase, methods, nlme Suggests: parallel License: GPL (>= 2) MD5sum: d95bde0855bed2eb25164cc2492f67b2 NeedsCompilation: no Title: Pathway Analysis with Down-weighting of Overlapping Genes (PADOG) Description: This package implements a general purpose gene set analysis method called PADOG that downplays the importance of genes that apear often accross the sets of genes to be analyzed. The package provides also a benchmark for gene set analysis methods in terms of sensitivity and ranking using 24 public datasets from KEGGdzPathwaysGEO package. biocViews: Microarray, OneChannel, TwoChannel, Bioinformatics Author: Adi Laurentiu Tarca Maintainer: Adi Laurentiu Tarca source.ver: src/contrib/PADOG_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PADOG_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PADOG_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PADOG_1.2.0.tgz vignettes: vignettes/PADOG/inst/doc/PADOG.pdf vignetteTitles: PADOG hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PADOG/inst/doc/PADOG.R Package: PAnnBuilder Version: 1.24.0 Depends: R (>= 2.7.0), methods, utils, RSQLite, Biobase (>= 1.17.0), AnnotationDbi (>= 1.3.12) Imports: methods, utils, Biobase, DBI, RSQLite, AnnotationDbi Suggests: org.Hs.ipi.db License: LGPL (>= 2.0) MD5sum: 6308008ae9d1ce6f7d035d63f91972d5 NeedsCompilation: no Title: Protein annotation data package builder Description: Processing annotation data from public data repositories and building protein-centric annotation data packages. biocViews: Annotation, Proteomics Author: Li Hong lihong@sibs.ac.cn Maintainer: Li Hong URL: http://www.biosino.org/PAnnBuilder source.ver: src/contrib/PAnnBuilder_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PAnnBuilder_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PAnnBuilder_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PAnnBuilder_1.24.0.tgz vignettes: vignettes/PAnnBuilder/inst/doc/fulltext.pdf, vignettes/PAnnBuilder/inst/doc/PAnnBuilder.pdf vignetteTitles: fulltext.pdf, Using the PAnnBuilder Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PAnnBuilder/inst/doc/PAnnBuilder.R Package: panp Version: 1.30.0 Depends: R (>= 2.10), affy (>= 1.23.4), Biobase (>= 2.5.5) Imports: Biobase, methods, stats, utils Suggests: gcrma License: GPL (>= 2) MD5sum: 7bb6c95888fdb3b71bcb120a3fa83ea6 NeedsCompilation: no Title: Presence-Absence Calls from Negative Strand Matching Probesets Description: A function to make gene presence/absence calls based on distance from negative strand matching probesets (NSMP) which are derived from Affymetrix annotation. PANP is applied after gene expression values are created, and therefore can be used after any preprocessing method such as MAS5 or GCRMA, or PM-only methods like RMA. NSMP sets have been established for the HGU133A and HGU133-Plus-2.0 chipsets to date. biocViews: Infrastructure Author: Peter Warren Maintainer: Peter Warren source.ver: src/contrib/panp_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/panp_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/panp_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/panp_1.30.0.tgz vignettes: vignettes/panp/inst/doc/panp.pdf vignetteTitles: gene presence/absence calls hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/panp/inst/doc/panp.R Package: PANR Version: 1.6.0 Depends: R (>= 2.14), igraph Imports: graphics, grDevices, MASS, methods, pvclust, stats, utils Suggests: snow, RedeR License: Artistic-2.0 MD5sum: 3552674a91e5a6aa51457f0801c9063b NeedsCompilation: no Title: Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations Description: This package provides S4 classes and methods for inferring functional gene networks with edges encoding posterior beliefs of gene association types and nodes encoding perturbation effects. biocViews: NetworkInference, NetworkVisualization, GraphsAndNetworks, Clustering, CellBasedAssays Author: Xin Wang Maintainer: Xin Wang source.ver: src/contrib/PANR_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PANR_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PANR_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PANR_1.6.0.tgz vignettes: vignettes/PANR/inst/doc/fullPAN.pdf, vignettes/PANR/inst/doc/PANR-Vignette.pdf, vignettes/PANR/inst/doc/pvmodule.pdf, vignettes/PANR/inst/doc/sigmod.pdf vignetteTitles: fullPAN.pdf, Main vignette:Posterior association network and enriched functional gene modules inferred from rich phenotypes of gene perturbations, pvmodule.pdf, sigmod.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PANR/inst/doc/PANR-Vignette.R suggestsMe: RedeR Package: PAPi Version: 1.0.0 Depends: R (>= 2.15.2), svDialogs, KEGGREST License: GPL(>= 2) MD5sum: d0a6ab0cd0876c26c8108ba9139757d7 NeedsCompilation: no Title: Predict metabolic pathway activity based on metabolomics data Description: The Pathway Activity Profiling - PAPi - is an R package for predicting the activity of metabolic pathways based solely on a metabolomics data set containing a list of metabolites identified and their respective abundances in different biological samples. PAPi generates hypothesis that improves the final biological interpretation. See Aggio, R.B.M; Ruggiero, K. and Villas-Boas, S.G. (2010) - Pathway Activity Profiling (PAPi): from metabolite profile to metabolic pathway activity. Bioinformatics. biocViews: MassSpectrometry, Metabolomics Author: Raphael Aggio Maintainer: Raphael Aggio source.ver: src/contrib/PAPi_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PAPi_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PAPi_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PAPi_1.0.0.tgz vignettes: vignettes/PAPi/inst/doc/PAPiPackage.pdf, vignettes/PAPi/inst/doc/PAPi.pdf vignetteTitles: Applying PAPi, PAPi.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PAPi/inst/doc/PAPiPackage.R Package: parody Version: 1.18.0 Depends: R (>= 2.5.0), methods, tools, utils License: Artistic-2.0 MD5sum: 5fae80d91493d5330b677a45485d1d90 NeedsCompilation: no Title: Parametric And Resistant Outlier DYtection Description: routines for univariate and multivariate outlier detection with a focus on parametric methods, but support for some methods based on resistant statistics biocViews: Bioinformatics, MultipleComparisons Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/parody_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/parody_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/parody_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/parody_1.18.0.tgz vignettes: vignettes/parody/inst/doc/parody.pdf vignetteTitles: parody: parametric and resistant outlier detection hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/parody/inst/doc/parody.R dependsOnMe: arrayMvout, flowQ Package: PathNet Version: 1.0.0 Depends: R (>= 1.14.0) Suggests: PathNetData, RUnit, BiocGenerics License: GPL-3 MD5sum: 786ad718d12f9dfb63c77f7d2e23b2a3 NeedsCompilation: no Title: An R package for pathway analysis using topological information Description: PathNet uses topological information present in pathways and differential expression levels of genes (obtained from microarray experiment) to identify pathways that are 1) significantly enriched and 2) associated with each other in the context of differential expression. The algorithm is described in: PathNet: A tool for pathway analysis using topological information. Dutta B, Wallqvist A, and Reifman J. Source Code for Biology and Medicine 2012 Sep 24;7(1):10. biocViews: Pathways, DifferentialExpression, MultipleComparisons Author: Bhaskar Dutta , Anders Wallqvist , and Jaques Reifman Maintainer: Jason B. Smith source.ver: src/contrib/PathNet_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PathNet_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PathNet_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PathNet_1.0.0.tgz vignettes: vignettes/PathNet/inst/doc/PathNet.pdf vignetteTitles: PathNet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PathNet/inst/doc/PathNet.R Package: pathRender Version: 1.28.0 Depends: graph, Rgraphviz, RColorBrewer, cMAP, AnnotationDbi, methods Suggests: ALL, hgu95av2.db License: LGPL MD5sum: d9aa206803bac0d9949a99d7ea919e6d NeedsCompilation: no Title: Render molecular pathways Description: build graphs from pathway databases, render them by Rgraphviz biocViews: GraphsAndNetworks, Pathways, NetworkVisualization Author: Li Long Maintainer: Li Long URL: http://www.bioconductor.org source.ver: src/contrib/pathRender_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pathRender_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pathRender_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pathRender_1.28.0.tgz vignettes: vignettes/pathRender/inst/doc/pathRender.pdf, vignettes/pathRender/inst/doc/plotExG.pdf vignetteTitles: pathRender overview, pathway graphs colored by expression map hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pathRender/inst/doc/pathRender.R, vignettes/pathRender/inst/doc/plotExG.R Package: pathview Version: 1.1.4 Depends: R (>= 2.10), KEGGgraph, org.Hs.eg.db Imports: Rgraphviz, graph, png, AnnotationDbi, methods, utils Suggests: gage, org.Mm.eg.db, RUnit, BiocGenerics License: GPL (>=3.0) MD5sum: aee2af78f9465c612be99038619a9e1f NeedsCompilation: no Title: a tool set for pathway based data integration and visualization Description: Pathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set analysis tools for large-scale and fully automated analysis. biocViews: Pathways, GraphsAndNetworks, NetworkVisualization, GeneSetEnrichment, DifferentialExpression, GeneExpression, Microarray, RNAseq, Genetics, Metabolomics, Proteomics, Bioinformatics Author: Weijun Luo Maintainer: Weijun Luo URL: http://pathview.r-forge.r-project.org/ source.ver: src/contrib/pathview_1.1.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/pathview_1.1.4.zip win64.binary.ver: bin/windows64/contrib/2.16/pathview_1.1.4.zip mac.binary.ver: bin/macosx/contrib/2.16/pathview_1.1.4.tgz vignettes: vignettes/pathview/inst/doc/pathview.pdf vignetteTitles: Pathview: pathway based data integration and visualization hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pathview/inst/doc/pathview.R suggestsMe: gage Package: pcaGoPromoter Version: 1.4.0 Depends: R (>= 2.14.0) , ellipse Imports: Biobase (>= 2.10.0) , AnnotationDbi Suggests: Rgraphviz, GO.db, hgu133plus2.db, mouse4302.db, rat2302.db, hugene10sttranscriptcluster.db, mogene10sttranscriptcluster.db, Biostrings, pcaGoPromoter.Hs.hg19, pcaGoPromoter.Mm.mm9, pcaGoPromoter.Rn.rn4, serumStimulation, parallel License: GPL (>= 2) MD5sum: 6148abc19de92b04748a48c75baa861f NeedsCompilation: no Title: pcaGoPromoter is used to analyze DNA micro array data Description: This package contains functions to ease the analyses of DNA micro arrays. It utilizes principal component analysis as the initial multivariate analysis, followed by functional interpretation of the principal component dimensions with overrepresentation analysis for GO terms and regulatory interpretations using overrepresentation analysis of predicted transcription factor binding sites with the primo algorithm. biocViews: GeneExpression, Microarray, GO , Visualization Author: Morten Hansen, Jorgen Olsen Maintainer: Morten Hansen source.ver: src/contrib/pcaGoPromoter_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pcaGoPromoter_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pcaGoPromoter_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pcaGoPromoter_1.4.0.tgz vignettes: vignettes/pcaGoPromoter/inst/doc/pcaGoPromoter.pdf vignetteTitles: pcaGoPromoter hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pcaGoPromoter/inst/doc/pcaGoPromoter.R Package: pcaMethods Version: 1.50.0 Depends: Biobase, methods, Rcpp (>= 0.8.7) Imports: BiocGenerics, MASS LinkingTo: Rcpp Suggests: matrixStats, lattice License: GPL (>= 3) Archs: i386, x64 MD5sum: 6516181e2d5886c8e504e15b976dfb54 NeedsCompilation: yes Title: A collection of PCA methods. Description: Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany. biocViews: Bioinformatics Author: Wolfram Stacklies, Henning Redestig, Kevin Wright Maintainer: Henning Redestig SystemRequirements: Rcpp source.ver: src/contrib/pcaMethods_1.50.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pcaMethods_1.50.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pcaMethods_1.50.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pcaMethods_1.50.0.tgz vignettes: vignettes/pcaMethods/inst/doc/missingValues.pdf, vignettes/pcaMethods/inst/doc/outliers.pdf, vignettes/pcaMethods/inst/doc/pcaMethods.pdf vignetteTitles: Missing value imputation, Data with outliers, Introduction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pcaMethods/inst/doc/missingValues.R, vignettes/pcaMethods/inst/doc/outliers.R, vignettes/pcaMethods/inst/doc/pcaMethods.R dependsOnMe: DeconRNASeq Package: pcot2 Version: 1.28.0 Depends: R (>= 2.0.0), grDevices, Biobase, amap Suggests: multtest, hu6800.db, KEGG.db, mvtnorm License: GPL (>= 2) MD5sum: c3d4653a0e6561b333c262dae52a4640 NeedsCompilation: no Title: Principal Coordinates and Hotelling's T-Square method Description: PCOT2 is a permutation-based method for investigating changes in the activity of multi-gene networks. It utilizes inter-gene correlation information to detect significant alterations in gene network activities. Currently it can be applied to two-sample comparisons. biocViews: Microarray, DifferentialExpression Author: Sarah Song, Mik Black Maintainer: Sarah Song source.ver: src/contrib/pcot2_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pcot2_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pcot2_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pcot2_1.28.0.tgz vignettes: vignettes/pcot2/inst/doc/HowToUseGeneLocator.pdf, vignettes/pcot2/inst/doc/pcot2.pdf vignetteTitles: HowToUseGeneLocator.pdf, PCOT2 Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pcot2/inst/doc/pcot2.R Package: PCpheno Version: 1.22.0 Depends: R (>= 2.10), Category, ScISI (>= 1.3.0), SLGI, ppiStats, ppiData, annotate (>= 1.17.4) Imports: AnnotationDbi, Biobase, Category, GO.db, graph, graphics, GSEABase, KEGG.db, methods, ScISI, stats, stats4 Suggests: KEGG.db, GO.db, org.Sc.sgd.db License: Artistic-2.0 MD5sum: 687103fdf86f7c69de17dbacd65c1802 NeedsCompilation: no Title: Phenotypes and cellular organizational units Description: Tools to integrate, annotate, and link phenotypes to cellular organizational units such as protein complexes and pathways. biocViews: GraphsAndNetworks, Proteomics, NetworkAnalysis Author: Nolwenn Le Meur and Robert Gentleman Maintainer: Nolwenn Le Meur source.ver: src/contrib/PCpheno_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PCpheno_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PCpheno_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PCpheno_1.22.0.tgz vignettes: vignettes/PCpheno/inst/doc/PCpheno.pdf vignetteTitles: PCpheno Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PCpheno/inst/doc/PCpheno.R Package: pdInfoBuilder Version: 1.24.0 Depends: R (>= 2.15.0), methods, Biobase (>= 2.17.7), RSQLite (>= 0.11.1), affxparser (>= 1.29.12), oligo (>= 1.21.5) Imports: Biostrings (>= 2.25.12), IRanges (>= 1.15.44) License: Artistic-2.0 Archs: i386, x64 MD5sum: 133942138297deaa4c242468b4e69dc4 NeedsCompilation: yes Title: Platform Design Information Package Builder Description: Builds platform design information packages. These consist of a SQLite database containing feature-level data such as x, y position on chip and featureSet ID. The database also incorporates featureSet-level annotation data. The products of this packages are used by the oligo pkg. biocViews: Annotation, Infrastructure Author: Seth Falcon, Benilton Carvalho with contributions by Vince Carey, Matt Settles and Kristof de Beuf Maintainer: Benilton Carvalho source.ver: src/contrib/pdInfoBuilder_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pdInfoBuilder_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pdInfoBuilder_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pdInfoBuilder_1.24.0.tgz vignettes: vignettes/pdInfoBuilder/inst/doc/BuildingPDInfoPkgs.pdf, vignettes/pdInfoBuilder/inst/doc/howto-AffymetrixMapping.pdf vignetteTitles: Building Annotation Packages with pdInfoBuilder for Use with the oligo Package, PDInfo Package Building Affymetrix Mapping Chips hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pdInfoBuilder/inst/doc/BuildingPDInfoPkgs.R, vignettes/pdInfoBuilder/inst/doc/howto-AffymetrixMapping.R Package: pdmclass Version: 1.32.0 Depends: Biobase (>= 1.4.22), R (>= 1.9.0), fibroEset, mda License: Artistic-2.0 MD5sum: 6150ecf604ab9373630dcb754224bd48 NeedsCompilation: no Title: Classification of Microarray Samples using Penalized Discriminant Methods Description: This package can be used to classify microarray data using one of three penalized regression methods; partial least squares, principal components regression, or ridge regression. biocViews: Classification Author: James W. MacDonald, Debashis Ghosh, based in part on pls code of Mike Denham Maintainer: James W. MacDonald source.ver: src/contrib/pdmclass_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pdmclass_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pdmclass_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pdmclass_1.32.0.tgz vignettes: vignettes/pdmclass/inst/doc/pdmclass.pdf vignetteTitles: pdmclass Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pdmclass/inst/doc/pdmclass.R suggestsMe: oneChannelGUI Package: PGSEA Version: 1.34.0 Depends: R (>= 2.10), GO.db, KEGG.db, AnnotationDbi, annaffy, methods, Biobase (>= 2.5.5) Suggests: GSEABase, GEOquery, org.Hs.eg.db, hgu95av2.db, limma License: GPL-2 MD5sum: 1737be0b7caa9ea87bc20850f9cd4cb0 NeedsCompilation: no Title: Parametric Gene Set Enrichment Analysis Description: Parametric Analysis of Gene Set Enrichment biocViews: Microarray Author: Kyle Furge and Karl Dykema Maintainer: Karl Dykema source.ver: src/contrib/PGSEA_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PGSEA_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PGSEA_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PGSEA_1.34.0.tgz vignettes: vignettes/PGSEA/inst/doc/PGSEA2.pdf, vignettes/PGSEA/inst/doc/PGSEA.pdf vignetteTitles: HOWTO: PGSEA Example Workflow, HOWTO: PGSEA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PGSEA/inst/doc/PGSEA2.R, vignettes/PGSEA/inst/doc/PGSEA.R dependsOnMe: GeneExpressionSignature Package: pgUtils Version: 1.32.0 Depends: R (>= 1.8.0), methods, RPostgreSQL (>= 0.1) Imports: methods, RPostgreSQL (>= 0.1) License: LGPL (>= 2) MD5sum: 224f694c449d43a132df6d62f58253a8 NeedsCompilation: no Title: Utility functions for PostgreSQL databases Description: Functions for creating PostgreSQL database tables, with auto incrementing primary keys, selection of foreign keys to allow referential integrity and a logging mechanism. biocViews: Infrastructure Author: Johannes Rainer Maintainer: Johannes Rainer source.ver: src/contrib/pgUtils_1.32.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/pgUtils_1.32.0.tgz vignettes: vignettes/pgUtils/inst/doc/pgUtils.pdf vignetteTitles: pgUtils.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: maDB Package: phenoDist Version: 1.8.0 Depends: R (>= 2.9.0), imageHTS, e1071 Suggests: GOstats, MASS License: LGPL-2.1 MD5sum: c3df82a2c1a66a1b85d02ca6b2e9e22d NeedsCompilation: no Title: Phenotypic distance measures Description: PhenoDist is designed for measuring phenotypic distance in image-based high-throughput screening, in order to identify strong phenotypes and to group treatments into functional clusters. biocViews: CellBasedAssays, Bioinformatics Author: Xian Zhang, Gregoire Pau, Wolfgang Huber, Michael Boutros Maintainer: Xian Zhang URL: http://www.dkfz.de/signaling, http://www.embl.de/research/units/genome_biology/huber/ source.ver: src/contrib/phenoDist_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/phenoDist_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/phenoDist_1.8.0.zip vignettes: vignettes/phenoDist/inst/doc/phenoDist.pdf vignetteTitles: Introduction to phenoDist hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/phenoDist/inst/doc/phenoDist.R Package: phenoTest Version: 1.8.1 Depends: R (>= 2.12.0), Biobase, methods, annotate, Heatplus, BMA Imports: survival, limma, Hmisc, gplots, Category, AnnotationDbi, hopach, biomaRt, GSEABase, genefilter, xtable, annotate, mgcv, SNPchip, hgu133a.db, HTSanalyzeR Suggests: GSEABase, KEGG.db, GO.db Enhances: parallel, org.Ce.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Hs.eg.db, org.Dm.eg.db License: GPL (>=2) MD5sum: 711ad83b074a78215439e56ce4b8656a NeedsCompilation: no Title: Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation. Description: Tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided. biocViews: Microarray, Bioinformatics, DifferentialExpression, MultipleComparisons, Clustering, Classification Author: Evarist Planet Maintainer: Evarist Planet source.ver: src/contrib/phenoTest_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/phenoTest_1.8.1.zip win64.binary.ver: bin/windows64/contrib/2.16/phenoTest_1.8.1.zip mac.binary.ver: bin/macosx/contrib/2.16/phenoTest_1.8.1.tgz vignettes: vignettes/phenoTest/inst/doc/phenoTest.pdf vignetteTitles: Manual for the phenoTest library hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/phenoTest/inst/doc/phenoTest.R Package: phyloseq Version: 1.4.5 Depends: R (>= 2.15.2), methods, ade4 (>= 1.4.17), picante (>= 1.5.2) Imports: ape (>= 3.0.7), Biostrings (>= 2.26.3), foreach (>= 1.4), ggplot2 (>= 0.9.3), igraph (>= 0.6.5.2), multtest (>= 2.14), plyr (>= 1.8), reshape (>= 0.8.4), RJSONIO (>= 1.0.1), scales (>= 0.2.3), vegan (>= 2.0.6) Suggests: genefilter (>= 1.40), testthat (>= 0.7) Enhances: doParallel (>= 1.0.1) License: AGPL-3 MD5sum: ba5ba19c4cb1c8421da8d9511a379943 NeedsCompilation: no Title: Handling and analysis of high-throughput microbiome census data. Description: phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data. biocViews: Clustering, Classification, MultipleComparisons, QualityControl, GeneticVariability, HighThroughputSequencing Author: Paul J. McMurdie , Susan Holmes , with contributions from Gregory Jordan and Scott Chamberlain Maintainer: Paul J. McMurdie URL: http://dx.plos.org/10.1371/journal.pone.0061217 source.ver: src/contrib/phyloseq_1.4.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/phyloseq_1.4.5.zip win64.binary.ver: bin/windows64/contrib/2.16/phyloseq_1.4.5.zip mac.binary.ver: bin/macosx/contrib/2.16/phyloseq_1.4.5.tgz vignettes: vignettes/phyloseq/inst/doc/phyloseq_analysis.pdf, vignettes/phyloseq/inst/doc/phyloseq_basics.pdf, vignettes/phyloseq/inst/doc/phyloseq_classes_7.pdf vignetteTitles: Analysis examples using phyloseq, Basic data manipulation using phyloseq, phyloseq_classes_7.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/phyloseq/inst/doc/phyloseq_analysis.R, vignettes/phyloseq/inst/doc/phyloseq_basics.R Package: piano Version: 1.0.7 Depends: R (>= 2.14.0) Imports: Biobase, gplots, igraph, relations, marray Suggests: yeast2.db, rsbml, plotrix, limma, affy, plier, affyPLM, gtools, biomaRt License: GPL (>=2) MD5sum: 2f568d2caa3cf7e58097c8cf97980a94 NeedsCompilation: no Title: Platform for integrative analysis of omics data Description: Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. Furthermore, the Piano package contains functions for combining the results of multiple runs of gene set analyses. biocViews: Microarray, Preprocessing, QualityControl, DifferentialExpression, DataImport, DataRepresentation, Visualization Author: Leif Varemo and Intawat Nookaew Maintainer: Leif Varemo URL: http://www.sysbio.se/piano source.ver: src/contrib/piano_1.0.7.tar.gz win.binary.ver: bin/windows/contrib/2.16/piano_1.0.7.zip win64.binary.ver: bin/windows64/contrib/2.16/piano_1.0.7.zip mac.binary.ver: bin/macosx/contrib/2.16/piano_1.0.7.tgz vignettes: vignettes/piano/inst/doc/piano-vignette.pdf vignetteTitles: Piano - Platform for Integrative Analysis of Omics data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/piano/inst/doc/piano-vignette.R Package: pickgene Version: 1.32.0 Imports: graphics, grDevices, MASS, stats, utils License: GPL (>= 2) MD5sum: 7b1e99022e09bf9dc6044ddf2b3cf57f NeedsCompilation: no Title: Adaptive Gene Picking for Microarray Expression Data Analysis Description: Functions to Analyze Microarray (Gene Expression) Data. biocViews: Microarray, DifferentialExpression Author: Brian S. Yandell Maintainer: Brian S. Yandell URL: http://www.stat.wisc.edu/~yandell/statgen source.ver: src/contrib/pickgene_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pickgene_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pickgene_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pickgene_1.32.0.tgz vignettes: vignettes/pickgene/inst/doc/pickgene.pdf vignetteTitles: Adaptive Gene Picking for Microarray Expression Data Analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pickgene/inst/doc/pickgene.R Package: PICS Version: 2.4.1 Depends: R (>= 2.14.0), BiocGenerics (>= 0.1.3) Imports: methods, stats4, IRanges, GenomicRanges, graphics, grDevices, stats, Rsamtools Suggests: ShortRead, rtracklayer, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: ca4c74975dc4b9f57fec2a2d3d4c7deb NeedsCompilation: yes Title: Probabilistic inference of ChIP-seq Description: Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach. biocViews: Clustering, Visualization, Sequencing, ChIPseq Author: Xuekui Zhang , Raphael Gottardo Maintainer: Renan Sauteraud source.ver: src/contrib/PICS_2.4.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/PICS_2.4.1.zip win64.binary.ver: bin/windows64/contrib/2.16/PICS_2.4.1.zip mac.binary.ver: bin/macosx/contrib/2.16/PICS_2.4.1.tgz vignettes: vignettes/PICS/inst/doc/PICS.pdf vignetteTitles: The PICS users guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PICS/inst/doc/PICS.R importsMe: PING Package: PING Version: 2.4.0 Depends: R(>= 2.15.0), chipseq, IRanges, GenomicRanges Imports: methods, PICS, graphics, grDevices, stats, Gviz, fda, BSgenome, stats4, BiocGenerics Suggests: parallel, ShortRead, rtracklayer License: Artistic-2.0 Archs: i386, x64 MD5sum: bb05159cb57848b31dd815654f098e02 NeedsCompilation: yes Title: Probabilistic inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data Description: Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach. biocViews: Clustering, Statistics, Visualization, Sequencing Author: Xuekui Zhang , Raphael Gottardo , Sangsoon Woo, Maintainer: Renan Sauteraud source.ver: src/contrib/PING_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PING_2.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PING_2.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PING_2.4.0.tgz vignettes: vignettes/PING/inst/doc/PING.pdf, vignettes/PING/inst/doc/PING-PE.pdf vignetteTitles: The PING users guide, Using PING with paired-end sequencing data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PING/inst/doc/PING-PE.R, vignettes/PING/inst/doc/PING.R Package: pint Version: 1.12.0 Depends: mvtnorm, methods, graphics, Matrix, dmt License: FreeBSD MD5sum: 03ae5183d48a3a6f9e5962902ebc8981 NeedsCompilation: no Title: Pairwise INTegration of functional genomics data Description: Pairwise data integration for functional genomics, including tools for DNA/RNA/miRNA dependency screens. biocViews: aCGH, GeneExpression, Genetics, DifferentialExpression, Microarray Author: Olli-Pekka Huovilainen and Leo Lahti Maintainer: Olli-Pekka Huovilainen source.ver: src/contrib/pint_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pint_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pint_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pint_1.12.0.tgz vignettes: vignettes/pint/inst/doc/depsearch.pdf vignetteTitles: pint hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/pint/inst/doc/depsearch.R Package: pkgDepTools Version: 1.26.0 Depends: methods, graph, RBGL Imports: graph, RBGL Suggests: Biobase, Rgraphviz, RCurl, BiocInstaller License: GPL-2 MD5sum: b5174eda4bfd2e5f9e856eaa0f6b0f36 NeedsCompilation: no Title: Package Dependency Tools Description: This package provides tools for computing and analyzing dependency relationships among R packages. It provides tools for building a graph-based representation of the dependencies among all packages in a list of CRAN-style package repositories. There are also utilities for computing installation order of a given package. If the RCurl package is available, an estimate of the download size required to install a given package and its dependencies can be obtained. biocViews: Infrastructure, GraphsAndNetworks Author: Seth Falcon Maintainer: Seth Falcon source.ver: src/contrib/pkgDepTools_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pkgDepTools_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pkgDepTools_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pkgDepTools_1.26.0.tgz vignettes: vignettes/pkgDepTools/inst/doc/pkgDepTools.pdf vignetteTitles: How to Use pkgDepTools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pkgDepTools/inst/doc/pkgDepTools.R Package: plateCore Version: 1.18.0 Depends: R (>= 2.10), flowCore, flowViz, lattice, latticeExtra Imports: Biobase, flowCore, graphics, grDevices, lattice, MASS, methods, robustbase, stats, utils Suggests: gplots License: Artistic-2.0 MD5sum: 5146311406ebbf0a60ee258d3933bacf NeedsCompilation: no Title: Statistical tools and data structures for plate-based flow cytometry Description: Provides basic S4 data structures and routines for analyzing plate based flow cytometry data. biocViews: FlowCytometry, Infrastructure, CellBasedAssays Author: Errol Strain, Florian Hahne, and Perry Haaland Maintainer: Errol Strain URL: http://www.bioconductor.org source.ver: src/contrib/plateCore_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/plateCore_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/plateCore_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/plateCore_1.18.0.tgz vignettes: vignettes/plateCore/inst/doc/expDens.pdf, vignettes/plateCore/inst/doc/plateCoreVig.pdf vignetteTitles: expDens.pdf, An R Package for Analysis of High Throughput Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plateCore/inst/doc/plateCoreVig.R Package: plgem Version: 1.32.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), MASS Imports: utils License: GPL-2 MD5sum: 558dad5d71368cc367530446265694fd NeedsCompilation: no Title: Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM) Description: The Power Law Global Error Model (PLGEM) has been shown to faithfully model the variance-versus-mean dependence that exists in a variety of genome-wide datasets, including microarray and proteomics data. The use of PLGEM has been shown to improve the detection of differentially expressed genes or proteins in these datasets. biocViews: Microarray, DifferentialExpression, Proteomics Author: Mattia Pelizzola and Norman Pavelka Maintainer: Norman Pavelka URL: http://www.genopolis.it source.ver: src/contrib/plgem_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/plgem_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/plgem_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/plgem_1.32.0.tgz vignettes: vignettes/plgem/inst/doc/plgem.pdf vignetteTitles: An introduction to PLGEM hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plgem/inst/doc/plgem.R Package: plier Version: 1.30.0 Depends: R (>= 2.0), methods Imports: affy, Biobase, methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 18a436e60c3696403d20f16f94d7bcf6 NeedsCompilation: yes Title: Implements the Affymetrix PLIER algorithm Description: The PLIER (Probe Logarithmic Error Intensity Estimate) method produces an improved signal by accounting for experimentally observed patterns in probe behavior and handling error at the appropriately at low and high signal values. biocViews: Software Author: Affymetrix Inc., Crispin J Miller, PICR Maintainer: Crispin Miller source.ver: src/contrib/plier_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/plier_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/plier_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/plier_1.30.0.tgz hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE suggestsMe: piano, virtualArray Package: PLPE Version: 1.20.0 Depends: R (>= 2.6.2), Biobase (>= 2.5.5), LPE, MASS, methods License: GPL (>= 2) MD5sum: 6eedfbca446a13c6428f51f7741e7858 NeedsCompilation: no Title: Local Pooled Error Test for Differential Expression with Paired High-throughput Data Description: This package performs tests for paired high-throughput data. biocViews: Proteomics, Microarray, DifferentialExpression Author: HyungJun Cho and Jae K. Lee Maintainer: Soo-heang Eo URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/PLPE_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PLPE_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PLPE_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PLPE_1.20.0.tgz vignettes: vignettes/PLPE/inst/doc/PLPE.pdf vignetteTitles: PLPE Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PLPE/inst/doc/PLPE.R Package: plrs Version: 1.0.0 Depends: R (>= 2.10), Biobase Imports: BiocGenerics, CGHbase, graphics, grDevices, ic.infer, marray, methods, quadprog, Rcsdp, stats, stats4, utils Suggests: mvtnorm, methods License: GPL (>=2.0) MD5sum: b82c642e63e4b2c90cf89826b5ee9182 NeedsCompilation: no Title: Piecewise Linear Regression Splines (PLRS) for the association between DNA copy number and gene expression Description: The present package implements a flexible framework for modeling the relationship between DNA copy number and gene expression data using Piecewise Linear Regression Splines (PLRS). Author: Gwenael G.R. Leday Maintainer: Gwenael G.R. Leday to source.ver: src/contrib/plrs_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/plrs_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/plrs_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/plrs_1.0.0.tgz vignettes: vignettes/plrs/inst/doc/plrs_vignette.pdf vignetteTitles: plrs hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plrs/inst/doc/plrs_vignette.R Package: plw Version: 1.20.0 Depends: R (>= 2.10), affy (>= 1.23.4) Imports: MASS, affy, graphics, splines, stats Suggests: limma License: GPL-2 Archs: i386, x64 MD5sum: 9eedb36006994a43f03d392a69e9a1b0 NeedsCompilation: yes Title: Probe level Locally moderated Weighted t-tests. Description: Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW). biocViews: Microarray, OneChannel, TwoChannel, Bioinformatics, DifferentialExpression Author: Magnus Astrand Maintainer: Magnus Astrand source.ver: src/contrib/plw_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/plw_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/plw_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/plw_1.20.0.tgz vignettes: vignettes/plw/inst/doc/HowToPLW.pdf vignetteTitles: HowTo plw hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plw/inst/doc/HowToPLW.R Package: ppiStats Version: 1.26.0 Depends: ScISI (>= 1.13.2), lattice, ppiData (>= 0.1.19) Imports: Biobase, Category, graph, graphics, grDevices, lattice, methods, RColorBrewer, stats Suggests: yeastExpData, xtable License: Artistic-2.0 MD5sum: ea8ed0b7fc52299c125cc0bdd3b5c90c NeedsCompilation: no Title: Protein-Protein Interaction Statistical Package Description: Tools for the analysis of protein interaction data. biocViews: Proteomics, GraphsAndNetworks, NetworkAnalysis Author: T. Chiang and D. Scholtens with contributions from W. Huber and L. Wang Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/ppiStats_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ppiStats_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ppiStats_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ppiStats_1.26.0.tgz vignettes: vignettes/ppiStats/inst/doc/ppiStats.pdf vignetteTitles: ppiStats hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ppiStats/inst/doc/ppiStats.R dependsOnMe: PCpheno suggestsMe: BiocCaseStudies, RpsiXML Package: prada Version: 1.36.1 Depends: R (>= 2.10.0), Biobase, RColorBrewer, grid, methods, rrcov Imports: Biobase, BiocGenerics, graphics, grDevices, grid, MASS, methods, RColorBrewer, rrcov, stats4, utils Suggests: cellHTS, tcltk License: LGPL Archs: i386, x64 MD5sum: f30e581e52dbc2711856e5765f06502d NeedsCompilation: yes Title: Data analysis for cell-based functional assays Description: Tools for analysing and navigating data from high-throughput phenotyping experiments based on cellular assays and fluorescent detection (flow cytometry (FACS), high-content screening microscopy). biocViews: CellBasedAssays, Visualization Author: Florian Hahne , Wolfgang Huber , Markus Ruschhaupt, Joern Toedling Maintainer: Florian Hahne URL: http://www.dkfz.de/mga/whuber, http://www.dkfz.de/LIFEdb source.ver: src/contrib/prada_1.36.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/prada_1.36.1.zip win64.binary.ver: bin/windows64/contrib/2.16/prada_1.36.1.zip mac.binary.ver: bin/macosx/contrib/2.16/prada_1.36.1.tgz vignettes: vignettes/prada/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/prada/inst/doc/norm2.R, vignettes/prada/inst/doc/prada2cellHTS.R htmlDocs: vignettes/prada/inst/doc/fcs3.html htmlTitles: "Data File Standard for Flow Cytometry, Version FCS3.0" dependsOnMe: cellHTS, domainsignatures, RNAither importsMe: cellHTS2 Package: prebs Version: 1.0.2 Depends: R (>= 2.14.0), Rsamtools, affy Imports: parallel, methods, stats, GenomicRanges, IRanges Suggests: prebsdata, hgu133plus2cdf, hgu133plus2probe License: Artistic-2.0 MD5sum: 38f3c8be879cfe5b8dc5333b17b00a42 NeedsCompilation: no Title: Probe region expression estimation for RNA-seq data for improved microarray comparability Description: The prebs package aims at making RNA-sequencing (RNA-seq) data more comparable to microarray data. The comparability is achieved by summarizing sequencing-based expressions of probe regions using a modified version of RMA algorithm. The pipeline takes mapped reads in BAM format as an input and produces either gene expressions or original microarray probe set expressions as an output. biocViews: Microarray, RNAseq, Sequencing, Bioinformatics, GeneExpression, Preprocessing Author: Karolis Uziela and Antti Honkela Maintainer: Karolis Uziela source.ver: src/contrib/prebs_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/prebs_1.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/prebs_1.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/prebs_1.0.2.tgz vignettes: vignettes/prebs/inst/doc/prebs.pdf vignetteTitles: prebs User Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/prebs/inst/doc/prebs.R Package: PREDA Version: 1.6.0 Depends: R (>= 2.9.0), Biobase, lokern (>= 1.0.9), multtest, stats, methods, annotate Suggests: quantsmooth, qvalue, samr, limma, caTools, affy, PREDAsampledata Enhances: Rmpi, rsprng License: GPL-2 MD5sum: 5723f11a1968c48b5de5f7321ef8ef5c NeedsCompilation: no Title: Position RElated Data Anlysis Description: Package for the position related analysis of quantitative functional genomics data. biocViews: Software, CopyNumberVariants, GeneExpression, Genetics Author: Francesco Ferrari Maintainer: Francesco Ferrari source.ver: src/contrib/PREDA_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PREDA_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PREDA_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PREDA_1.6.0.tgz vignettes: vignettes/PREDA/inst/doc/PREDAclasses.pdf, vignettes/PREDA/inst/doc/PREDAtutorial.pdf vignetteTitles: PREDA S4-classes, PREDA tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PREDA/inst/doc/PREDAclasses.R, vignettes/PREDA/inst/doc/PREDAtutorial.R Package: predictionet Version: 1.6.1 Depends: igraph, catnet Imports: penalized, RBGL, MASS Suggests: network, minet, knitr License: Artistic-2.0 MD5sum: 4f9204af8fec85f9a96b85e92d76d129 NeedsCompilation: yes Title: Inference for predictive networks designed for (but not limited to) genomic data Description: This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases. The main function is able to generate networks using Bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer networks with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen. biocViews: GraphsAndNetworks, NetworkInference Author: Benjamin Haibe-Kains, Catharina Olsen, Gianluca Bontempi, John Quackenbush Maintainer: Benjamin Haibe-Kains , Catharina Olsen URL: http://compbio.dfci.harvard.edu, http://www.ulb.ac.be/di/mlg source.ver: src/contrib/predictionet_1.6.1.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/predictionet_1.6.1.tgz vignettes: vignettes/predictionet/inst/doc/predictionet-boxplotr2pwcvfig2.pdf, vignettes/predictionet/inst/doc/predictionet-boxplotstabpwcvfig2.pdf, vignettes/predictionet/inst/doc/predictionet-cytoscape.pdf, vignettes/predictionet/inst/doc/predictionet-edgecoldiffig.pdf, vignettes/predictionet/inst/doc/predictionet-edgestabfig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabmccfig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabmcctestfig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabr2fig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabr2testfig.pdf, vignettes/predictionet/inst/doc/predictionet.pdf, vignettes/predictionet/inst/doc/predictionet-pn_webapp_ras.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvpriorsweightfig2.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvtopo1topo2fig2.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvtopo1topo2predfig2.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvtopo1topo2stabfig2.pdf, vignettes/predictionet/inst/doc/predictionet-regrnet_design.pdf, vignettes/predictionet/inst/doc/predictionet-regrnetopofig.pdf vignetteTitles: predictionet-boxplotr2pwcvfig2.pdf, predictionet-boxplotstabpwcvfig2.pdf, predictionet-cytoscape.pdf, predictionet-edgecoldiffig.pdf, predictionet-edgestabfig.pdf, predictionet-genepredabmccfig.pdf, predictionet-genepredabmcctestfig.pdf, predictionet-genepredabr2fig.pdf, predictionet-genepredabr2testfig.pdf, predictionet, predictionet-pn_webapp_ras.pdf, predictionet-regnetcvpriorsweightfig2.pdf, predictionet-regnetcvtopo1topo2fig2.pdf, predictionet-regnetcvtopo1topo2predfig2.pdf, predictionet-regnetcvtopo1topo2stabfig2.pdf, predictionet-regrnet_design.pdf, predictionet-regrnetopofig.pdf hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/predictionet/inst/doc/predictionet.R Package: preprocessCore Version: 1.22.0 Depends: methods Imports: stats License: LGPL (>= 2) Archs: i386, x64 MD5sum: 61621ddcbf5a682ff116e9159e5b821e NeedsCompilation: yes Title: A collection of pre-processing functions Description: A library of core preprocessing routines biocViews: Infrastructure Author: Benjamin Milo Bolstad Maintainer: Benjamin Milo Bolstad source.ver: src/contrib/preprocessCore_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/preprocessCore_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/preprocessCore_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/preprocessCore_1.22.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affyPLM, cqn, crlmm, RefPlus, virtualArray importsMe: affy, AffyTiling, charm, cn.farms, frma, frmaTools, lumi, MBCB, minfi, MSnbase, oligo, waveTiling suggestsMe: oneChannelGUI Package: PROcess Version: 1.36.0 Depends: Icens Imports: graphics, grDevices, Icens, stats, utils License: Artistic-2.0 MD5sum: cfc5f7ec443081e8a6ffa3bbe8bf78a6 NeedsCompilation: no Title: Ciphergen SELDI-TOF Processing Description: A package for processing protein mass spectrometry data. biocViews: MassSpectrometry, Proteomics Author: Xiaochun Li Maintainer: Xiaochun Li source.ver: src/contrib/PROcess_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PROcess_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PROcess_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PROcess_1.36.0.tgz vignettes: vignettes/PROcess/inst/doc/howtoprocess.pdf vignetteTitles: HOWTO PROcess hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PROcess/inst/doc/howtoprocess.R Package: procoil Version: 1.10.0 Depends: R (>= 2.10.1), methods Imports: methods, stats, graphics, utils Suggests: Biostrings License: GPL (>= 2) MD5sum: f3f49036ef94f6a4228d2ed9a5d2fa21 NeedsCompilation: no Title: Prediction of Oligomerization of Coiled Coil Proteins Description: The procoil package allows to predict whether a coiled coil sequence (amino acid sequence plus heptad register) is more likely to form a dimer or more likely to form a trimer. The predict function not only computes the prediction itself, but also a profile which allows to determine the strengths to which the individual residues are indicative for either class. Profiles can also be plotted and exported to files. biocViews: Proteomics, Classification Author: Ulrich Bodenhofer Maintainer: Ulrich Bodenhofer URL: http://www.bioinf.jku.at/software/procoil/ source.ver: src/contrib/procoil_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/procoil_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/procoil_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/procoil_1.10.0.tgz vignettes: vignettes/procoil/inst/doc/procoil.pdf vignetteTitles: PrOCoil - A Web Service and an R Package for Predicting the Oligomerization of Coiled-Coil Proteins hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/procoil/inst/doc/procoil.R Package: pRoloc Version: 1.0.1 Depends: R (>= 2.15), MSnbase (>= 1.7.23), MLInterfaces (>= 1.37.1), methods Imports: mclust, MSBVAR, caret, e1071, sampling, class, kernlab, lattice, nnet, randomForest, proxy, BiocGenerics, stats4, RColorBrewer, scales, MASS, knitr Suggests: testthat, pRolocdata, roxygen2 License: GPL-2 MD5sum: 9fb0048014225a6ed7bd066bac3a5a1a NeedsCompilation: no Title: A unifying bioinformatics framework for spatial proteomics Description: This package implements pattern recognition techniques on quantitiative mass spectrometry data to infer protein sub-cellular localisation. Author: Laurent Gatto and Lisa M. Breckels with contributions from Thomas Burger and Samuel Wieczorek Maintainer: Laurent Gatto VignetteBuilder: knitr source.ver: src/contrib/pRoloc_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/pRoloc_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/pRoloc_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/pRoloc_1.0.1.tgz vignettes: vignettes/pRoloc/inst/doc/pRoloc-tutorial.pdf vignetteTitles: pRoloc tutorial hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pRoloc/inst/doc/pRoloc-tutorial.R Package: PROMISE Version: 1.12.0 Depends: R (>= 2.11.0), Biobase, GSEABase Imports: Biobase, GSEABase, stats License: GPL (>= 2) MD5sum: 632258a338a49a08e1f7a3ecd59dcabc NeedsCompilation: no Title: PRojection Onto the Most Interesting Statistical Evidence Description: A general tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables as described in Pounds et. al. (2009) Bioinformatics 25: 2013-2019 biocViews: Microarray, OneChannel, Bioinformatics, MultipleComparisons, GeneExpression Author: Stan Pounds , Xueyuan Cao Maintainer: Stan Pounds , Xueyuan Cao source.ver: src/contrib/PROMISE_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PROMISE_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PROMISE_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PROMISE_1.12.0.tgz vignettes: vignettes/PROMISE/inst/doc/PROMISE.pdf vignetteTitles: An introduction to PROMISE hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PROMISE/inst/doc/PROMISE.R Package: proteinProfiles Version: 1.0.0 Depends: R (>= 2.15.2) Imports: graphics, stats Suggests: testthat License: GPL-3 MD5sum: 43a39a6bcec46cbbc9c8bc026693de95 NeedsCompilation: no Title: Protein Profiling Description: Significance assessment for distance measures of time-course protein profiles Author: Julian Gehring Maintainer: Julian Gehring source.ver: src/contrib/proteinProfiles_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/proteinProfiles_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/proteinProfiles_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/proteinProfiles_1.0.0.tgz vignettes: vignettes/proteinProfiles/inst/doc/proteinProfiles.pdf vignetteTitles: The proteinProfiles package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/proteinProfiles/inst/doc/proteinProfiles.R Package: puma Version: 3.2.1 Depends: R (>= 2.10), Biobase (>= 2.5.5), affy (>= 1.23.4), graphics, grDevices, methods, stats, utils, mclust Imports: Biobase (>= 2.5.5), affy (>= 1.23.4),affyio Suggests: pumadata, affydata, snow, limma, annotate, ROCR License: LGPL Archs: i386, x64 MD5sum: ce75b7e12f9f5c2a63c6160c1b87c9e3 NeedsCompilation: yes Title: Propagating Uncertainty in Microarray Analysis Description: Most analyses of Affymetrix GeneChip data are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting and data manipulation functions. biocViews: Microarray, OneChannel, Preprocessing, Bioinformatics, DifferentialExpression, Clustering Author: Richard D. Pearson, Xuejun Liu, Magnus Rattray, Marta Milo, Neil D. Lawrence, Guido Sanguinetti, Li Zhang Maintainer: Richard Pearson URL: http://umber.sbs.man.ac.uk/resources/puma source.ver: src/contrib/puma_3.2.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/puma_3.2.1.zip win64.binary.ver: bin/windows64/contrib/2.16/puma_3.2.1.zip mac.binary.ver: bin/macosx/contrib/2.16/puma_3.2.1.tgz vignettes: vignettes/puma/inst/doc/puma-014.pdf, vignettes/puma/inst/doc/puma-015.pdf, vignettes/puma/inst/doc/puma-016.pdf, vignettes/puma/inst/doc/puma-022.pdf, vignettes/puma/inst/doc/puma-023.pdf, vignettes/puma/inst/doc/puma-024.pdf, vignettes/puma/inst/doc/puma.pdf vignetteTitles: puma-014.pdf, puma-015.pdf, puma-016.pdf, puma-022.pdf, puma-023.pdf, puma-024.pdf, puma.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE importsMe: tigre suggestsMe: tigre Package: pvac Version: 1.8.0 Depends: R (>= 2.8.0) Imports: affy (>= 1.20.0), stats, Biobase Suggests: pbapply, affydata, ALLMLL, genefilter License: LGPL (>= 2.0) MD5sum: 4245b849a0426d5c7c37ae37cefe07d2 NeedsCompilation: no Title: PCA-based gene filtering for Affymetrix arrays Description: The package contains the function for filtering genes by the proportion of variation accounted for by the first principal component (PVAC). biocViews: Bioinformatics, Microarray, OneChannel, QualityControl Author: Jun Lu and Pierre R. Bushel Maintainer: Jun Lu , Pierre R. Bushel source.ver: src/contrib/pvac_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/pvac_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/pvac_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/pvac_1.8.0.tgz vignettes: vignettes/pvac/inst/doc/density.pdf, vignettes/pvac/inst/doc/pvac.pdf vignetteTitles: density.pdf, PCA-based gene filtering for Affymetrix GeneChips hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pvac/inst/doc/pvac.R Package: pvca Version: 1.0.1 Depends: R (>= 2.15.1) Imports: Matrix, Biobase, vsn, lme4 Suggests: golubEsets License: LGPL (>= 2.0) MD5sum: a9b67d638b41bb9dbc749873d95672ed NeedsCompilation: no Title: Principal Variance Component Analysis (PVCA) Description: This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12. biocViews: Bioinformatics, Microarray, BatchEffectAssessment Author: Pierre Bushel Maintainer: Jianying LI source.ver: src/contrib/pvca_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/pvca_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/pvca_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/pvca_1.0.1.tgz vignettes: vignettes/pvca/inst/doc/pvcaEstimate.pdf, vignettes/pvca/inst/doc/pvca.pdf vignetteTitles: pvcaEstimate.pdf, Batch effect estimation in Microarray data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pvca/inst/doc/pvca.R Package: PWMEnrich Version: 2.2.0 Depends: methods, grid, BiocGenerics, Biostrings, Imports: seqLogo, gdata, evd Suggests: MotifDb, BSgenome.Dmelanogaster.UCSC.dm3, PWMEnrich.Dmelanogaster.background, testthat, gtools, parallel License: GPL-3 MD5sum: 60bec88605c7cf30f60aff509da431d6 NeedsCompilation: no Title: PWM enrichment analysis Description: Asses the enrichment of already known PWMs (from JASPAR and MotifDb) in DNA sequences. The package implements multiple algorithms, including fixed-threshold (Z-score) and threshold-free (Lognormal normalization and Clover) methods. These can be applied to a single sequence (e.g. enhancer of interest) or a group of sequences (e.g. a set of ChIP-chip/seq peaks). The output is a ranked list of PWMs according to their level of enrichment compared to genomic background. Custom sets of PWMs and genomic background are also supported. biocViews: Bioinformatics, SequenceMatching, GenomicSequence, Software Author: Robert Stojnic, with contributions from Diego Diez Maintainer: Robert Stojnic source.ver: src/contrib/PWMEnrich_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/PWMEnrich_2.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/PWMEnrich_2.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/PWMEnrich_2.2.0.tgz vignettes: vignettes/PWMEnrich/inst/doc/PWMEnrich.pdf vignetteTitles: Overview of the 'PWMEnrich' package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PWMEnrich/inst/doc/PWMEnrich.R Package: qpcrNorm Version: 1.18.0 Depends: methods, Biobase, limma, affy License: LGPL (>= 2) MD5sum: a99410f522b841c18389af29476209a4 NeedsCompilation: no Title: Data-driven normalization strategies for high-throughput qPCR data. Description: The package contains functions to perform normalization of high-throughput qPCR data. Basic functions for processing raw Ct data plus functions to generate diagnostic plots are also available. biocViews: Preprocessing, GeneExpression Author: Jessica Mar Maintainer: Jessica Mar source.ver: src/contrib/qpcrNorm_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/qpcrNorm_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/qpcrNorm_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/qpcrNorm_1.18.0.tgz vignettes: vignettes/qpcrNorm/inst/doc/qpcrNorm.pdf vignetteTitles: qPCR Normalization Example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qpcrNorm/inst/doc/qpcrNorm.R suggestsMe: EasyqpcR Package: qpgraph Version: 1.16.3 Depends: R (>= 2.14.0) Imports: methods, Matrix (>= 1.0), graphics, annotate, graph (>= 1.37.6), Biobase, GGBase, AnnotationDbi, mvtnorm, qtl, Rgraphviz Suggests: genefilter, org.EcK12.eg.db Enhances: rlecuyer, snow, Category, GOstats License: GPL (>= 2) Archs: i386, x64 MD5sum: f55c8baefe14ef25d42a2a890d51566b NeedsCompilation: yes Title: Reverse engineering of molecular regulatory networks with qp-graphs Description: q-order partial correlation graphs, or qp-graphs for short, are undirected Gaussian graphical Markov models built from q-order partial correlations. They are useful for learning undirected graphical Gaussian Markov models from data sets where the number of random variables p exceeds the available sample size n as, for instance, in the case of microarray data where they can be employed to reverse engineer a molecular regulatory network. biocViews: Microarray, GeneExpression, Transcription, Pathways, NetworkInference, GraphsAndNetworks, GeneRegulation Author: R. Castelo and A. Roverato Maintainer: Robert Castelo URL: http://functionalgenomics.upf.edu/qpgraph source.ver: src/contrib/qpgraph_1.16.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/qpgraph_1.16.3.zip win64.binary.ver: bin/windows64/contrib/2.16/qpgraph_1.16.3.zip mac.binary.ver: bin/macosx/contrib/2.16/qpgraph_1.16.3.tgz vignettes: vignettes/qpgraph/inst/doc/BasicUsersGuide.pdf, vignettes/qpgraph/inst/doc/qpgraphSimulate.pdf, vignettes/qpgraph/inst/doc/qpTxRegNet.pdf vignetteTitles: BasicUsersGuide.pdf, Simulating molecular regulatory networks using qpgraph, Reverse-engineer transcriptional regulatory networks using qpgraph hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qpgraph/inst/doc/qpgraphSimulate.R, vignettes/qpgraph/inst/doc/qpTxRegNet.R importsMe: clipper Package: qrqc Version: 1.14.0 Depends: reshape, ggplot2, Biostrings, biovizBase, brew, xtable, Rsamtools (>= 1.3.28), testthat Imports: reshape, ggplot2, Biostrings, biovizBase, graphics, methods, plyr, stats LinkingTo: Rsamtools License: GPL (>=2) Archs: i386, x64 MD5sum: bda2d62f1e6e7de871f20f581d96e86c NeedsCompilation: yes Title: Quick Read Quality Control Description: Quickly scans reads and gathers statistics on base and quality frequencies, read length, k-mers by position, and frequent sequences. Produces graphical output of statistics for use in quality control pipelines, and an optional HTML quality report. S4 SequenceSummary objects allow specific tests and functionality to be written around the data collected. biocViews: Sequencing, QualityControl, DataImport, Preprocessing, Visualization, HighThroughputSequencing Author: Vince Buffalo Maintainer: Vince Buffalo URL: http://github.com/vsbuffalo/qrqc source.ver: src/contrib/qrqc_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/qrqc_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/qrqc_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/qrqc_1.14.0.tgz vignettes: vignettes/qrqc/inst/doc/qrqc.pdf vignetteTitles: Using the qrqc package to gather information about sequence qualities hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qrqc/inst/doc/qrqc.R Package: QUALIFIER Version: 1.4.0 Depends: R (>= 2.14.0),reshape,flowWorkspace,flowViz,flowCore,RColorBrewer Imports: MASS,hwriter,RSVGTipsDevice,lattice,stats4,flowCore,flowViz,methods,flowWorkspace,reshape Enhances: ncdfFlow License: Artistic-2.0 MD5sum: e1da0133a7cae4daa059d3097dde2ba0 NeedsCompilation: no Title: Qualitiy Control of Gated Flow Cytometry Experiments Description: Provides quality control and quality assessment tools for gated flow cytometry data. biocViews: Infrastructure, Flowcytometry, CellBasedAssays Author: Mike Jiang,Greg Finak,Raphael Gottardo Maintainer: Mike Jiang source.ver: src/contrib/QUALIFIER_1.4.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/QUALIFIER_1.4.0.tgz vignettes: vignettes/QUALIFIER/inst/doc/QUALIFIER.pdf vignetteTitles: Quality assessment for gated Flow Cytometry Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/QUALIFIER/inst/doc/QUALIFIER.R Package: quantsmooth Version: 1.26.0 Depends: R(>= 2.10.0), quantreg, grid License: GPL-2 MD5sum: e169aa26eebbb3522a691cca7d1ac2bf NeedsCompilation: no Title: Quantile smoothing and genomic visualization of array data Description: Implements quantile smoothing as introduced in: Quantile smoothing of array CGH data; Eilers PH, de Menezes RX; Bioinformatics. 2005 Apr 1;21(7):1146-53. biocViews: Visualization, CopyNumberVariants Author: Jan Oosting, Paul Eilers, Renee Menezes Maintainer: Jan Oosting source.ver: src/contrib/quantsmooth_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/quantsmooth_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/quantsmooth_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/quantsmooth_1.26.0.tgz vignettes: vignettes/quantsmooth/inst/doc/quantsmooth.pdf vignetteTitles: quantsmooth hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/quantsmooth/inst/doc/quantsmooth.R dependsOnMe: beadarraySNP importsMe: GWASTools, SIM suggestsMe: PREDA Package: QuasR Version: 1.0.9 Depends: R (>= 2.15.0), parallel, GenomicRanges, Rbowtie (>= 0.99.0) Imports: methods, zlibbioc, BiocGenerics, IRanges, BiocInstaller, Biobase, Biostrings, GenomicRanges, BSgenome, Rsamtools, GenomicFeatures, ShortRead LinkingTo: Rsamtools Suggests: Rsamtools, rtracklayer, Gviz, RUnit License: GPL-2 Archs: i386, x64 MD5sum: 37891aa8d8d09e249a936619e65aae94 NeedsCompilation: yes Title: Quantify and Annotate Short Reads in R Description: This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest. biocViews: Genetics, Preprocessing, HighThroughputSequencing, ChIPseq, RNAseq, Methylseq Author: Anita Lerch, Dimos Gaiditzis and Michael Stadler Maintainer: Michael Stadler source.ver: src/contrib/QuasR_1.0.9.tar.gz win.binary.ver: bin/windows/contrib/2.16/QuasR_1.0.9.zip win64.binary.ver: bin/windows64/contrib/2.16/QuasR_1.0.9.zip mac.binary.ver: bin/macosx/contrib/2.16/QuasR_1.0.9.tgz vignettes: vignettes/QuasR/inst/doc/QuasR-Overview.pdf vignetteTitles: An introduction to QuasR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/QuasR/inst/doc/QuasR-Overview.R Package: qvalue Version: 1.34.0 Imports: graphics, grDevices, stats, tcltk License: LGPL MD5sum: d3530337fff4c8aaa220d1a20652bbef NeedsCompilation: no Title: Q-value estimation for false discovery rate control Description: This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining. biocViews: MultipleComparisons Author: Alan Dabney and John D. Storey , with assistance from Gregory R. Warnes Maintainer: John D. Storey source.ver: src/contrib/qvalue_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/qvalue_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/qvalue_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/qvalue_1.34.0.tgz vignettes: vignettes/qvalue/inst/doc/manual.pdf, vignettes/qvalue/inst/doc/pHist.pdf, vignettes/qvalue/inst/doc/qHist.pdf, vignettes/qvalue/inst/doc/qPlots.pdf, vignettes/qvalue/inst/doc/qvalue.pdf vignetteTitles: manual.pdf, pHist.pdf, qHist.pdf, qPlots.pdf, qvalue Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qvalue/inst/doc/qvalue.R dependsOnMe: anota, CancerMutationAnalysis, DEGseq, DrugVsDisease, netresponse, SSPA, webbioc importsMe: anota, DOSE, ReactomePA, synapter, trigger, webbioc suggestsMe: LBE, maanova, PREDA Package: r3Cseq Version: 1.6.0 Depends: GenomicRanges,Rsamtools,data.table,rtracklayer,VGAM,qvalue,RColorBrewer,sqldf,methods Suggests: BSgenome.Mmusculus.UCSC.mm9,BSgenome.Hsapiens.UCSC.hg18,BSgenome.Hsapiens.UCSC.hg19 License: GPL-3 MD5sum: c921d8816e82008c69aeac97a03722cc NeedsCompilation: no Title: Analysis of Chromosome Conformation Capture and Next-generation Sequencing (3C-seq) Description: This package is an implementation of data analysis for the long-range interactions from 3C-seq assay. biocViews: Preprocessing, Sequencing, HighThroughputSequencing Author: Supat Thongjuea, Bergen Center for Computational Science, Norway Maintainer: Supat Thongjuea URL: http://r3cseq.genereg.net source.ver: src/contrib/r3Cseq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/r3Cseq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/r3Cseq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/r3Cseq_1.6.0.tgz vignettes: vignettes/r3Cseq/inst/doc/r3Cseq.pdf vignetteTitles: r3Cseq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/r3Cseq/inst/doc/r3Cseq.R Package: R453Plus1Toolbox Version: 1.10.0 Depends: R (>= 2.12.0), BiocGenerics, Biobase, Biostrings, BSgenome.Scerevisiae.UCSC.sacCer2,TeachingDemos Imports: BiocGenerics (>= 0.1.3), Biobase (>= 2.15.1), biomaRt, Biostrings, BSgenome, IRanges (>= 1.17.24), methods, R2HTML, Rsamtools, rtracklayer, ShortRead, VariantAnnotation, xtable, tools Suggests: rtracklayer, ShortRead, Rsamtools, BSgenome.Hsapiens.UCSC.hg19 License: LGPL-3 Archs: i386, x64 MD5sum: 961ebc360e1e506e6354e80cd7d31853 NeedsCompilation: yes Title: A package for importing and analyzing data from Roche's Genome Sequencer System. Description: The R453Plus1 Toolbox comprises useful functions for the analysis of data generated by Roche's 454 sequencing platform. It adds functions for quality assurance as well as for annotation and visualization of detected variants, complementing the software tools shipped by Roche with their product. Further, a pipeline for the detection of structural variants is provided. biocViews: HighThroughputSequencing, Infrastructure, DataImport, DataRepresentation, Visualization, QualityControl, ReportWriting Author: Hans-Ulrich Klein, Christoph Bartenhagen, Christian Ruckert Maintainer: Hans-Ulrich Klein source.ver: src/contrib/R453Plus1Toolbox_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/R453Plus1Toolbox_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/R453Plus1Toolbox_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/R453Plus1Toolbox_1.10.0.tgz vignettes: vignettes/R453Plus1Toolbox/inst/doc/vignette.pdf vignetteTitles: A package for importing and analyzing data from Roche's Genome Sequencer System hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/R453Plus1Toolbox/inst/doc/vignette.R Package: rama Version: 1.34.0 Depends: R(>= 2.5.0) License: GPL (>= 2) Archs: i386, x64 MD5sum: 46effc91b81b7f41e21d31a37418e5e5 NeedsCompilation: yes Title: Robust Analysis of MicroArrays Description: Robust estimation of cDNA microarray intensities with replicates. The package uses a Bayesian hierarchical model for the robust estimation. Outliers are modeled explicitly using a t-distribution, and the model also addresses classical issues such as design effects, normalization, transformation, and nonconstant variance. biocViews: Microarray, TwoChannel, QualityControl, Preprocessing Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/rama_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rama_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rama_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rama_1.34.0.tgz vignettes: vignettes/rama/inst/doc/rama.pdf vignetteTitles: rama Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rama/inst/doc/rama.R dependsOnMe: bridge Package: RamiGO Version: 1.6.0 Depends: gsubfn,methods Imports: igraph,RCurl,png,RCytoscape,graph License: Artistic-2.0 MD5sum: 1814130070590338821e99351abedd84 NeedsCompilation: no Title: AmiGO visualize R interface Description: R interface sending requests to AmiGO visualize, retrieving DAG GO trees, parsing GraphViz DOT format files and exporting GML files for Cytoscape. Also uses RCytoscape to interactively display AmiGO trees in Cytoscape. biocViews: GO, NetworkVisualization, GraphsAndNetworks, Classification, ConnectTools Author: Markus Schroeder, Daniel Gusenleitner, John Quackenbush, Aedin Culhane, Benjamin Haibe-Kains Maintainer: Markus Schroeder source.ver: src/contrib/RamiGO_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RamiGO_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RamiGO_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RamiGO_1.6.0.tgz vignettes: vignettes/RamiGO/inst/doc/RamiGO.pdf vignetteTitles: RamiGO: An Introduction (HowTo) hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RamiGO/inst/doc/RamiGO.R Package: randPack Version: 1.6.0 Depends: methods Imports: Biobase License: Artistic 2.0 MD5sum: d670d77e39b8265b4573a4cada2fb872 NeedsCompilation: no Title: Randomization routines for Clinical Trials Description: A suite of classes and functions for randomizing patients in clinical trials. biocViews: Statistics Author: Vincent Carey and Robert Gentleman Maintainer: Robert Gentleman source.ver: src/contrib/randPack_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/randPack_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/randPack_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/randPack_1.6.0.tgz vignettes: vignettes/randPack/inst/doc/randPack.pdf vignetteTitles: Clinical trial randomization infrastructure hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/randPack/inst/doc/randPack.R Package: RankProd Version: 2.32.0 Depends: R (>= 1.9.0) Imports: graphics License: file LICENSE License_restricts_use: yes MD5sum: 6be88ddf703352d0eb1b4555cb2fd9ac NeedsCompilation: no Title: Rank Product method for identifying differentially expressed genes with application in meta-analysis Description: Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification. biocViews: DifferentialExpression Author: Fangxin Hong and Ben Wittner with contribution from Rainer Breitling , Colin Smith , and Florian Battke Maintainer: Fangxin Hong source.ver: src/contrib/RankProd_2.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RankProd_2.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RankProd_2.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RankProd_2.32.0.tgz vignettes: vignettes/RankProd/inst/doc/RankProd.pdf vignetteTitles: RankProd Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RankProd/inst/doc/RankProd.R dependsOnMe: RNAither importsMe: HTSanalyzeR suggestsMe: oneChannelGUI Package: RbcBook1 Version: 1.28.0 Depends: R (>= 2.10), Biobase, graph, rpart License: Artistic-2.0 MD5sum: 4fb6500eb8c61915d0ec0171ca08e542 NeedsCompilation: no Title: Support for Springer monograph on Bioconductor Description: tools for building book biocViews: Software Author: Vince Carey and Wolfgang Huber Maintainer: Vince Carey URL: http://www.biostat.harvard.edu/~carey source.ver: src/contrib/RbcBook1_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RbcBook1_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RbcBook1_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RbcBook1_1.28.0.tgz vignettes: vignettes/RbcBook1/inst/doc/RbcBook1.pdf vignetteTitles: RbcBook1 Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RbcBook1/inst/doc/RbcBook1.R Package: RBGL Version: 1.36.2 Depends: graph, methods Imports: methods Suggests: Rgraphviz, XML License: Artistic-2.0 Archs: i386, x64 MD5sum: 5e1bfbf8be747e85939b6b75642f1489 NeedsCompilation: yes Title: An interface to the BOOST graph library Description: A fairly extensive and comprehensive interface to the graph algorithms contained in the BOOST library. biocViews: GraphsAndNetworks, NetworkAnalysis Author: Vince Carey , Li Long , R. Gentleman Maintainer: Bioconductor Package Maintainer URL: http://www.bioconductor.org source.ver: src/contrib/RBGL_1.36.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/RBGL_1.36.2.zip win64.binary.ver: bin/windows64/contrib/2.16/RBGL_1.36.2.zip mac.binary.ver: bin/macosx/contrib/2.16/RBGL_1.36.2.tgz vignettes: vignettes/RBGL/inst/doc/filedep.pdf, vignettes/RBGL/inst/doc/RBGL.pdf vignetteTitles: filedep.pdf, RBGL Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RBGL/inst/doc/RBGL.R dependsOnMe: apComplex, BioNet, CellNOptR, flowWorkspace, joda, pkgDepTools, RpsiXML importsMe: biocViews, CAMERA, Category, clipper, DEGraph, GeneAnswers, GOstats, NCIgraph, nem, OrganismDbi, pkgDepTools, predictionet, Streamer, VariantTools suggestsMe: BiocCaseStudies, DEGraph, graph, KEGGgraph Package: RBioinf Version: 1.20.0 Depends: graph, methods Suggests: Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: ef090015c63e494b09456509a762150f NeedsCompilation: yes Title: RBioinf Description: Functions and datasets and examples to accompany the monograph R For Bioinformatics. biocViews: GeneExpression, Microarray, Preprocessing, QualityControl, Classification, Clustering, MultipleComparison, Annotation Author: Robert Gentleman Maintainer: Robert Gentleman source.ver: src/contrib/RBioinf_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RBioinf_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RBioinf_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RBioinf_1.20.0.tgz vignettes: vignettes/RBioinf/inst/doc/RBioinf.pdf vignetteTitles: RBioinf Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RBioinf/inst/doc/RBioinf.R Package: rBiopaxParser Version: 1.0.0 Imports: XML Suggests: Rgraphviz, RCurl, graph, RUnit, BiocGenerics License: GPL (>= 2) MD5sum: cd67a147c839544282e4aa5e37f17e87 NeedsCompilation: no Title: Parses BioPax files and represents them in R Description: Parses BioPAX files and represents them in R, at the moment BioPAX level 2 and level 3 are supported. Author: Frank Kramer Maintainer: Frank Kramer URL: https://github.com/frankkramer/rBiopaxParser source.ver: src/contrib/rBiopaxParser_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rBiopaxParser_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rBiopaxParser_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rBiopaxParser_1.0.0.tgz vignettes: vignettes/rBiopaxParser/inst/doc/biopax2classgraph.pdf, vignettes/rBiopaxParser/inst/doc/biopaxsimple.pdf, vignettes/rBiopaxParser/inst/doc/mergedpw.pdf, vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.pdf, vignettes/rBiopaxParser/inst/doc/segclock.pdf, vignettes/rBiopaxParser/inst/doc/wntplot.pdf vignetteTitles: biopax2classgraph.pdf, biopaxsimple.pdf, mergedpw.pdf, rBiopaxParser Vignette, segclock.pdf, wntplot.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.R Package: Rbowtie Version: 1.0.3 Suggests: parallel License: Artistic-1.0 | file LICENSE MD5sum: 98b0a0f96a539b8f8b7b937b6920d8e7 NeedsCompilation: yes Title: R bowtie wrapper Description: This package provides an R wrapper around the popular bowtie short read aligner and around SpliceMap, a de novo splice junction discovery and alignment tool. The package is used by the QuasR bioconductor package. We recommend to use the QuasR package instead of using Rbowtie directly. biocViews: HighThroughputSequencing Author: Florian Hahne, Anita Lerch, Michael B Stadler Maintainer: Michael Stadler source.ver: src/contrib/Rbowtie_1.0.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rbowtie_1.0.3.zip win64.binary.ver: bin/windows64/contrib/2.16/Rbowtie_1.0.3.zip mac.binary.ver: bin/macosx/contrib/2.16/Rbowtie_1.0.3.tgz vignettes: vignettes/Rbowtie/inst/doc/Rbowtie-Overview.pdf vignetteTitles: An introduction to Rbowtie hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/Rbowtie/inst/doc/Rbowtie-Overview.R dependsOnMe: QuasR Package: rbsurv Version: 2.18.0 Depends: R (>= 2.5.0), Biobase (>= 2.5.5), survival License: GPL (>= 2) MD5sum: bd68e19b06db29fb14ade03787f122b4 NeedsCompilation: no Title: Robust likelihood-based survival modeling with microarray data Description: This package selects genes associated with survival. biocViews: Microarray, Bioinformatics Author: HyungJun Cho , Sukwoo Kim , Soo-heang Eo , Jaewoo Kang Maintainer: Soo-heang Eo URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/rbsurv_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rbsurv_2.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rbsurv_2.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rbsurv_2.18.0.tgz vignettes: vignettes/rbsurv/inst/doc/rbsurv.pdf vignetteTitles: Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rbsurv/inst/doc/rbsurv.R Package: Rcade Version: 1.2.0 Depends: R (>= 2.14.0), methods, GenomicRanges, baySeq, Rsamtools Imports: graphics, IRanges, rgl Suggests: limma, biomaRt, RUnit, BiocGenerics License: GPL-2 MD5sum: 95798ea081d56a0b00cb2991fa61f3b8 NeedsCompilation: no Title: R-based analysis of ChIP-seq And Differential Expression - a tool for integrating a count-based ChIP-seq analysis with differential expression summary data. Description: Rcade (which stands for "R-based analysis of ChIP-seq And Differential Expression") is a tool for integrating ChIP-seq data with differential expression summary data, through a Bayesian framework. A key application is in identifing the genes targeted by a transcription factor of interest - that is, we collect genes that are associated with a ChIP-seq peak, and differential expression under some perturbation related to that TF. biocViews: DifferentialExpression, GeneExpression, Transcription, ChIPseq, Sequencing, Genetics Author: Jonathan Cairns Maintainer: Jonathan Cairns source.ver: src/contrib/Rcade_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rcade_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Rcade_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Rcade_1.2.0.tgz vignettes: vignettes/Rcade/inst/doc/Rcade.pdf vignetteTitles: Rcade Vignette hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rcade/inst/doc/Rcade.R Package: RCASPAR Version: 1.6.0 License: GPL (>=3) MD5sum: 00db6d45f682155eeb6850f5bb175e60 NeedsCompilation: no Title: A package for survival time prediction based on a piecewise baseline hazard Cox regression model. Description: The package is the R-version of the C-based software \bold{CASPAR} (Kaderali,2006: \url{http://bioinformatics.oxfordjournals.org/content/22/12/1495}). It is meant to help predict survival times in the presence of high-dimensional explanatory covariates. The model is a piecewise baseline hazard Cox regression model with an Lq-norm based prior that selects for the most important regression coefficients, and in turn the most relevant covariates for survival analysis. It was primarily tried on gene expression and aCGH data, but can be used on any other type of high-dimensional data and in disciplines other than biology and medicine. biocViews: aCGH, GeneExpression, Genetics, Proteomics, Visualization Author: Douaa Mugahid Maintainer: Douaa Mugahid , Lars Kaderali source.ver: src/contrib/RCASPAR_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RCASPAR_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RCASPAR_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RCASPAR_1.6.0.tgz vignettes: vignettes/RCASPAR/inst/doc/RCASPAR.pdf vignetteTitles: RCASPAR: Software for high-dimentional-data driven survival time prediction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RCASPAR/inst/doc/RCASPAR.R Package: RchyOptimyx Version: 1.4.0 Depends: R (>= 2.10), Rgraphviz (>= 2.2.1) Imports: Rgraphviz, sfsmisc, graphics, methods, graph, grDevices Suggests: flowCore, flowType License: Artistic-2.0 Archs: i386, x64 MD5sum: 4eb0a980c5248a921333fe27e0bdfd95 NeedsCompilation: yes Title: Optimyzed Cellular Hierarchies for Flow Cytometry Description: Constructs a hierarchy of cells using flow cytometry for maximization of an external variable (e.g., a clinical outcome or a cytokine response). biocViews: FlowCytometry Author: Adrin Jalali, Nima Aghaeepour Maintainer: Adrin Jalali , Nima Aghaeepour source.ver: src/contrib/RchyOptimyx_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RchyOptimyx_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RchyOptimyx_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RchyOptimyx_1.4.0.tgz vignettes: vignettes/RchyOptimyx/inst/doc/RchyOptimyx.pdf vignetteTitles: flowType package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RchyOptimyx/inst/doc/RchyOptimyx.R Package: RCytoscape Version: 1.10.0 Depends: R (>= 2.14.0), graph (>= 1.31.0), XMLRPC (>= 0.2.4) Imports: methods, XMLRPC, BiocGenerics Suggests: RUnit License: GPL-2 MD5sum: 3a6bbc0f998e4ed34788ded85b56a0d3 NeedsCompilation: no Title: Display and manipulate graphs in Cytoscape Description: Interactvive viewing and exploration of graphs, connecting R to Cytoscape. biocViews: NetworkVisualization, GraphsAndNetworks, ConnectTools Author: Paul Shannon Maintainer: Paul Shannon URL: http://rcytoscape.systemsbiology.net source.ver: src/contrib/RCytoscape_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RCytoscape_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RCytoscape_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RCytoscape_1.10.0.tgz vignettes: vignettes/RCytoscape/inst/doc/RCytoscape.pdf vignetteTitles: RCytoscape Overview hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RCytoscape/inst/doc/RCytoscape.R importsMe: categoryCompare, NCIgraph suggestsMe: clipper, GeneNetworkBuilder, graphite Package: Rdisop Version: 1.20.0 Depends: R (>= 2.0.0), RcppClassic, Rcpp LinkingTo: RcppClassic, Rcpp Suggests: RUnit License: GPL-2 Archs: i386, x64 MD5sum: 8bf8f28bad3ea0bdde4a2613cd43968f NeedsCompilation: yes Title: Decomposition of Isotopic Patterns Description: Identification of metabolites using high precision mass spectrometry. MS Peaks are used to derive a ranked list of sum formulae, alternatively for a given sum formula the theoretical isotope distribution can be calculated to search in MS peak lists. biocViews: MassSpectrometry Author: Anton Pervukhin , Steffen Neumann Maintainer: Steffen Neumann URL: http://msbi.ipb-halle.de/ SystemRequirements: None source.ver: src/contrib/Rdisop_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rdisop_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Rdisop_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Rdisop_1.20.0.tgz vignettes: vignettes/Rdisop/inst/doc/Rdisop.pdf vignetteTitles: Molecule Identification with Rdisop hasREADME: FALSE hasNEWS: FALSE hasINSTALL: TRUE hasLICENSE: FALSE Rfiles: vignettes/Rdisop/inst/doc/Rdisop.R suggestsMe: MSnbase Package: RDRToolbox Version: 1.10.0 Depends: R (>= 2.9.0),rgl Imports: graphics, grDevices, methods, stats, MASS, rgl Suggests: golubEsets License: GPL (>= 2) MD5sum: 373e1a9e1d2afede39a866e08896a9cd NeedsCompilation: no Title: A package for nonlinear dimension reduction with Isomap and LLE. Description: A package for nonlinear dimension reduction using the Isomap and LLE algorithm. It also includes a routine for computing the Davis-Bouldin-Index for cluster validation, a plotting tool and a data generator for microarray gene expression data and for the Swiss Roll dataset. biocViews: Dimension,DimensionReduction,FeatureExtraction,Visualization,ClusterValidation,Microarray Author: Christoph Bartenhagen Maintainer: Christoph Bartenhagen source.ver: src/contrib/RDRToolbox_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RDRToolbox_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RDRToolbox_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RDRToolbox_1.10.0.tgz vignettes: vignettes/RDRToolbox/inst/doc/plot3D.pdf, vignettes/RDRToolbox/inst/doc/RDRToolbox-003.pdf, vignettes/RDRToolbox/inst/doc/SwissRoll.pdf, vignettes/RDRToolbox/inst/doc/vignette.pdf vignetteTitles: plot3D.pdf, RDRToolbox-003.pdf, SwissRoll.pdf, A package for nonlinear dimension reduction with Isomap and LLE. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RDRToolbox/inst/doc/vignette.R Package: ReactomePA Version: 1.4.0 Depends: R (>= 2.10), DOSE Imports: methods, AnnotationDbi, reactome.db, org.Hs.eg.db, stats4, plyr, igraph, qvalue, graphics Suggests: clusterProfiler, GOSemSim, org.Hs.eg.db License: GPL-2 MD5sum: 0758869c25c57172390abeeed26b6446 NeedsCompilation: no Title: Reactome Pathway Analysis Description: This package provides functions for pathway analysis based on REACTOME pathway database. It will implement enrichment analysis, gene set enrichment analysis and functional modules detection. biocViews: Bioinformatics, Pathways, Visualization Author: Guangchuang Yu Maintainer: Guangchuang Yu source.ver: src/contrib/ReactomePA_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ReactomePA_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ReactomePA_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ReactomePA_1.4.0.tgz vignettes: vignettes/ReactomePA/inst/doc/cnetplot.pdf, vignettes/ReactomePA/inst/doc/ReactomePA.pdf, vignettes/ReactomePA/inst/doc/rPAclusterProfiler.pdf vignetteTitles: cnetplot.pdf, An introduction to ReactomePA, rPAclusterProfiler.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReactomePA/inst/doc/ReactomePA.R suggestsMe: clusterProfiler, DOSE Package: ReadqPCR Version: 1.6.0 Depends: R(>= 2.14.0), Biobase, methods, affy Imports: Biobase Suggests: qpcR License: LGPL-3 MD5sum: ab23372a68375fc0a0d15c20184ffc99 NeedsCompilation: no Title: Read qPCR data Description: The package provides functions to read raw RT-qPCR data of different platforms. biocViews: DataImport, MicrotitrePlateAssay, GeneExpression, qPCR Author: James Perkins, Matthias Kohl, Nor Izayu Abdul Rahman Maintainer: James Perkins URL: http://www.bioconductor.org/packages/release/bioc/html/ReadqPCR.html source.ver: src/contrib/ReadqPCR_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ReadqPCR_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ReadqPCR_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ReadqPCR_1.6.0.tgz vignettes: vignettes/ReadqPCR/inst/doc/ReadqPCR.pdf vignetteTitles: Functions to load RT-qPCR data into R hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReadqPCR/inst/doc/ReadqPCR.R dependsOnMe: NormqPCR importsMe: NormqPCR Package: reb Version: 1.38.0 Depends: R (>= 2.0), Biobase, idiogram (>= 1.5.3) License: GPL-2 Archs: i386, x64 MD5sum: b3d3337c35350fc94a9ee01255fa91e9 NeedsCompilation: yes Title: Regional Expression Biases Description: A set of functions to dentify regional expression biases biocViews: Microarray, CopyNumberVariants, Visualization Author: Kyle A. Furge and Karl Dykema Maintainer: Karl J. Dykema source.ver: src/contrib/reb_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/reb_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/reb_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/reb_1.38.0.tgz vignettes: vignettes/reb/inst/doc/reb.pdf vignetteTitles: Smoothing of Microarray Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/reb/inst/doc/reb.R Package: RedeR Version: 1.8.3 Depends: R (>= 2.15), methods, igraph Imports: RCurl, XML, XMLRPC, rJava Suggests: JavaGD, PANR, pvclust License: GPL (>= 2) MD5sum: 469c92ef1030e5d9ffc108705b16fa29 NeedsCompilation: no Title: Interactive visualization and manipulation of nested networks. Description: RedeR is an R-based package combined with a stand-alone Java application for interactive visualization and manipulation of modular structures, nested networks and multiple levels of hierarchical associations. It implements a callback engine by using a low-level R-to-Java interface to build and run common plugins. In this sense, RedeR takes advantage of R to run robust statistics, while the R-to-Java interface bridges the gap between network analysis and visualization. biocViews: GraphsAndNetworks, NetworkVisualization, Networks, Software, Visualization Author: Mauro Castro, Xin Wang, Florian Markowetz Maintainer: Mauro Castro URL: http://genomebiology.com/2012/13/4/R29 source.ver: src/contrib/RedeR_1.8.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/RedeR_1.8.3.zip win64.binary.ver: bin/windows64/contrib/2.16/RedeR_1.8.3.zip mac.binary.ver: bin/macosx/contrib/2.16/RedeR_1.8.3.tgz vignettes: vignettes/RedeR/inst/doc/fig1.pdf, vignettes/RedeR/inst/doc/fig2.pdf, vignettes/RedeR/inst/doc/fig3.pdf, vignettes/RedeR/inst/doc/fig4.pdf, vignettes/RedeR/inst/doc/fig5a.pdf, vignettes/RedeR/inst/doc/fig5b.pdf, vignettes/RedeR/inst/doc/fig5c.pdf, vignettes/RedeR/inst/doc/fig6.pdf, vignettes/RedeR/inst/doc/RedeR.pdf vignetteTitles: fig1.pdf, fig2.pdf, fig3.pdf, fig4.pdf, fig5a.pdf, fig5b.pdf, fig5c.pdf, fig6.pdf, Main vignette: RedeR Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RedeR/inst/doc/RedeR.R suggestsMe: PANR Package: REDseq Version: 1.6.0 Depends: R (>= 2.15.0), BiocGenerics (>= 0.1.0), BSgenome.Celegans.UCSC.ce2, multtest, Biostrings, BSgenome, ChIPpeakAnno Imports: BiocGenerics, AnnotationDbi, Biostrings, ChIPpeakAnno, graphics, IRanges (>= 1.13.5), multtest, stats, utils License: GPL (>=2) MD5sum: 158ee1e82b0b2ab379a2d4ba492d6ccf NeedsCompilation: no Title: Analysis of high-throughput sequencing data processed by restriction enzyme digestion Description: The package includes functions to build restriction enzyme cut site (RECS) map, distribute mapped sequences on the map with five different approaches, find enriched/depleted RECSs for a sample, and identify differentially enriched/depleted RECSs between samples. biocViews: Sequencing, SequenceMatching, Preprocessing Author: Lihua Julie Zhu and Thomas Fazzio Maintainer: Lihua Julie Zhu source.ver: src/contrib/REDseq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/REDseq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/REDseq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/REDseq_1.6.0.tgz vignettes: vignettes/REDseq/inst/doc/REDseq.pdf vignetteTitles: REDseq Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/REDseq/inst/doc/REDseq.R Package: RefPlus Version: 1.30.0 Depends: R (>= 2.8.0), Biobase (>= 2.1.0), affy (>= 1.20.0), affyPLM (>= 1.18.0), preprocessCore (>= 1.4.0) Suggests: affydata License: GPL (>= 2) MD5sum: 7b798d58ed19576a30871b14872b77d0 NeedsCompilation: no Title: A function set for the Extrapolation Strategy (RMA+) and Extrapolation Averaging (RMA++) methods. Description: The package contains functions for pre-processing Affymetrix data using the RMA+ and the RMA++ methods. biocViews: Microarray, OneChannel, Preprocessing Author: Kai-Ming Chang , Chris Harbron , Marie C South Maintainer: Kai-Ming Chang source.ver: src/contrib/RefPlus_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RefPlus_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RefPlus_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RefPlus_1.30.0.tgz vignettes: vignettes/RefPlus/inst/doc/An_Exploration_of_Extensions_to_the_RMA_Algorithm.pdf, vignettes/RefPlus/inst/doc/Extensions_to_RMA_Algorithm.pdf, vignettes/RefPlus/inst/doc/RefPlus.pdf vignetteTitles: An_Exploration_of_Extensions_to_the_RMA_Algorithm.pdf, Extensions_to_RMA_Algorithm.pdf, RefPlus Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RefPlus/inst/doc/RefPlus.R Package: Repitools Version: 1.6.0 Depends: R (>= 2.13.0), methods, BiocGenerics (>= 0.1.0), GenomicRanges (>= 1.7.8) Imports: BiocGenerics, IRanges (>= 1.13.5), GenomicRanges, BSgenome, gplots, grid, MASS, gsmoothr, edgeR (>= 2.99.2), DNAcopy, Ringo, aroma.affymetrix, Rsolnp, snowfall, parallel Suggests: GenomicRanges, IRanges, BSgenome, gplots, grid, MASS, gsmoothr, edgeR, DNAcopy, Ringo, aroma.affymetrix, ShortRead, BSgenome.Hsapiens.UCSC.hg18, rtracklayer License: LGPL (>= 2) Archs: i386, x64 MD5sum: 9c42d78766845824b2ee5ac543121d24 NeedsCompilation: yes Title: Epigenomic tools Description: Tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, BayMeth for quantifying methylation etc. biocViews: DNAMethylation, GeneExpression, Methylseq Author: Mark Robinson , Dario Strbenac , Aaron Statham , Andrea Riebler Maintainer: Mark Robinson source.ver: src/contrib/Repitools_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Repitools_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Repitools_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Repitools_1.6.0.tgz vignettes: vignettes/Repitools/inst/doc/qc-cpgPlot.pdf, vignettes/Repitools/inst/doc/qc-enrPlot.pdf, vignettes/Repitools/inst/doc/Repitools_vignette.pdf, vignettes/Repitools/inst/doc/visualisations-binPlotsHeatmap.pdf, vignettes/Repitools/inst/doc/visualisations-binPlotsLine.pdf, vignettes/Repitools/inst/doc/visualisations-cluPlots3.pdf, vignettes/Repitools/inst/doc/visualisations-profPlots.pdf vignetteTitles: qc-cpgPlot.pdf, qc-enrPlot.pdf, Using Repitools for Epigenomic Sequencing Data, visualisations-binPlotsHeatmap.pdf, visualisations-binPlotsLine.pdf, visualisations-cluPlots3.pdf, visualisations-profPlots.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Repitools/inst/doc/Repitools_vignette.R Package: ReportingTools Version: 2.0.1 Depends: methods Imports: Biobase,hwriter,Category,GOstats,limma,lattice,AnnotationDbi,edgeR, annotate,PFAM.db, GSEABase, BiocGenerics(>= 0.1.6), grid, XML, R.utils, ggplot2, ggbio Suggests: RUnit, ggplot2, ggbio, ALL, hgu95av2.db, org.Mm.eg.db, knitr License: Artistic-2.0 MD5sum: b31b9e8d9ab3c646db498ae0e02b3c0c NeedsCompilation: no Title: Tools for making reports in various formats Description: The ReportingTools software package enables users to easily display reports of analysis results generated from sources such as microarray and sequencing data. The package allows users to create HTML pages that may be viewed on a web browser such as Safari, or in other formats readable by programs such as Excel. Users can generate tables with sortable and filterable columns, make and display plots, and link table entries to other data sources such as NCBI or larger plots within the HTML page. Using the package, users can also produce a table of contents page to link various reports together for a particular project that can be viewed in a web browser. biocViews: Bioinformatics, Software, Visualization, Microarray, RNAseq, GO Author: Jason A. Hackney, Melanie Huntley, Jessica L. Larson, Christina Chaivorapol, Gabriel Becker, and Josh Kaminker Maintainer: Jason A. Hackney , Gabriel Becker VignetteBuilder: utils, knitr source.ver: src/contrib/ReportingTools_2.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/ReportingTools_2.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/ReportingTools_2.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/ReportingTools_2.0.1.tgz vignettes: vignettes/ReportingTools/inst/doc/basicReportingTools.pdf, vignettes/ReportingTools/inst/doc/microarrayAnalysis.pdf, vignettes/ReportingTools/inst/doc/rnaseqAnalysis.pdf, vignettes/ReportingTools/inst/doc/shiny.pdf vignetteTitles: ReportingTools basics, Reporting on microarray differential expression, Reporting on RNA-seq differential expression, ReportingTools shiny hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReportingTools/inst/doc/basicReportingTools.R, vignettes/ReportingTools/inst/doc/knitr.R, vignettes/ReportingTools/inst/doc/microarrayAnalysis.R, vignettes/ReportingTools/inst/doc/rnaseqAnalysis.R, vignettes/ReportingTools/inst/doc/shiny.R htmlDocs: vignettes/ReportingTools/inst/doc/knitr.html htmlTitles: "Knitr and ReportingTools" importsMe: affycoretools suggestsMe: GSEABase Package: ReQON Version: 1.6.0 Depends: R (>= 2.15.0), Rsamtools, seqbias Imports: rJava, graphics, stats, utils, grDevices License: GPL-2 MD5sum: 33a43006c83ddd3aacae7eed92188cb6 NeedsCompilation: no Title: Recalibrating Quality Of Nucleotides Description: Algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format. biocViews: Sequencing, HighThroughputSequencing, Preprocessing, QualityControl Author: Christopher Cabanski, Keary Cavin, Chris Bizon Maintainer: Christopher Cabanski SystemRequirements: Java version >= 1.6 source.ver: src/contrib/ReQON_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ReQON_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ReQON_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ReQON_1.6.0.tgz vignettes: vignettes/ReQON/inst/doc/ReQON.pdf vignetteTitles: ReQON Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReQON/inst/doc/ReQON.R Package: Resourcerer Version: 1.34.0 Depends: R (>= 1.9.0), Biobase, AnnotationDbi (>= 1.4.0) Suggests: human.db0, mouse.db0, rat.db0 License: LGPL MD5sum: 9167691a413c7436cf395f2bf4f45400 NeedsCompilation: no Title: Reads annotation data from TIGR Resourcerer or convert the annotation data into Bioconductor data pacakge. Description: This package allows user either to read an annotation data file from TIGR Resourcerer as a matrix or convert the file into a Bioconductor annotation data package using the AnnBuilder package. biocViews: Annotation, Microarray Author: Jianhua Zhang Maintainer: Jianhua Zhang source.ver: src/contrib/Resourcerer_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Resourcerer_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Resourcerer_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Resourcerer_1.34.0.tgz vignettes: vignettes/Resourcerer/inst/doc/Resourcerer.pdf vignetteTitles: Resourcerer Resourcerer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Resourcerer/inst/doc/Resourcerer.R Package: rGADEM Version: 2.8.0 Depends: R (>= 2.11.0), Biostrings, IRanges, BSgenome, methods, seqLogo Imports: Biostrings, IRanges, methods, graphics, seqLogo Suggests: BSgenome.Hsapiens.UCSC.hg18 License: Artistic-2.0 Archs: i386, x64 MD5sum: 612c353dd7ded5b999290aee77f43d16 NeedsCompilation: yes Title: de novo motif discovery Description: rGADEM is an efficient de novo motif discovery tool for large-scale genomic sequence data. It is an open-source R package, which is based on the GADEM software. biocViews: Microarray, ChIPchip, Sequencing, ChIPseq, GenomicSequence, MotifDiscovery Author: Arnaud Droit, Raphael Gottardo, Gordon Robertson and Leiping Li Maintainer: Arnaud Droit source.ver: src/contrib/rGADEM_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rGADEM_2.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rGADEM_2.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rGADEM_2.8.0.tgz vignettes: vignettes/rGADEM/inst/doc/rGADEM.pdf vignetteTitles: The rGADEM users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rGADEM/inst/doc/rGADEM.R importsMe: MotIV Package: RGalaxy Version: 1.4.0 Depends: XML, methods, tools, optparse, digest, Imports: BiocGenerics, Biobase, roxygen2 Suggests: RUnit, hgu95av2.db, knitr, formatR, Rserve Enhances: RSclient License: Artistic-2.0 MD5sum: fb4aa61ad603b1e2c9216893f03336b5 NeedsCompilation: no Title: Make an R function available in the Galaxy web platform Description: Given an R function and its manual page, make the documented function available in Galaxy. biocViews: Infrastructure Author: The Bioconductor Dev Team Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/RGalaxy_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RGalaxy_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RGalaxy_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RGalaxy_1.4.0.tgz vignettes: vignettes/RGalaxy/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RGalaxy/inst/doc/RGalaxy-vignette.R htmlDocs: vignettes/RGalaxy/inst/doc/RGalaxy-vignette.html htmlTitles: "Introduction to RGalaxy" Package: Rgraphviz Version: 2.4.1 Depends: R (>= 2.6.0), methods, utils, graph, grid Imports: stats4, graph, graphics, grDevices, grid, methods, utils Suggests: RUnit, BiocGenerics, XML License: file LICENSE Archs: i386, x64 MD5sum: 288cd3a17c4fed8af183aa3852be9428 NeedsCompilation: yes Title: Provides plotting capabilities for R graph objects Description: Interfaces R with the AT and T graphviz library for plotting R graph objects from the graph package. biocViews: GraphsAndNetworks, NetworkVisualization Author: Jeff Gentry, Li Long, Robert Gentleman, Seth Falcon, Florian Hahne, Deepayan Sarkar, Kasper Daniel Hansen Maintainer: Kasper Daniel Hansen SystemRequirements: Graphviz (>= 2.16) source.ver: src/contrib/Rgraphviz_2.4.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rgraphviz_2.4.1.zip win64.binary.ver: bin/windows64/contrib/2.16/Rgraphviz_2.4.1.zip mac.binary.ver: bin/macosx/contrib/2.16/Rgraphviz_2.4.1.tgz vignettes: vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.pdf, vignettes/Rgraphviz/inst/doc/Rgraphviz.pdf vignetteTitles: A New Interface to Plot Graphs Using Rgraphviz, How To Plot A Graph Using Rgraphviz hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.R, vignettes/Rgraphviz/inst/doc/Rgraphviz.R dependsOnMe: biocGraph, BioMVCClass, CellNOptR, flowMerge, GOFunction, hyperdraw, MineICA, nem, netresponse, pathRender, RchyOptimyx, ROntoTools, SplicingGraphs, TDARACNE importsMe: apComplex, biocGraph, DEGraph, GOFunction, nem, pathview, qpgraph, RchyOptimyx, SplicingGraphs suggestsMe: altcdfenvs, annotate, BiocCaseStudies, Category, CNORfeeder, CNORfuzzy, ddgraph, DEGraph, flowCore, flowMerge, GeneNetworkBuilder, geneplotter, GlobalAncova, globaltest, GOstats, GSEABase, KEGGgraph, MLP, NCIgraph, oneChannelGUI, pcaGoPromoter, pkgDepTools, RBGL, RBioinf, rBiopaxParser, Rtreemix, safe, SPIA, SRAdb, Streamer, topGO Package: rhdf5 Version: 2.4.0 Depends: methods Imports: zlibbioc Suggests: bit64 License: Artistic-2.0 Archs: i386, x64 MD5sum: 3067565522c9fd20c4207b11b2c929fa NeedsCompilation: yes Title: HDF5 interface to R Description: This R/Bioconductor package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM. biocViews: Infrastructure Author: Bernd Fischer, Gregoire Pau Maintainer: Bernd Fischer SystemRequirements: GNU make source.ver: src/contrib/rhdf5_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rhdf5_2.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rhdf5_2.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rhdf5_2.4.0.tgz vignettes: vignettes/rhdf5/inst/doc/rhdf5.pdf vignetteTitles: rhdf5 hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rhdf5/inst/doc/rhdf5.R Package: rHVDM Version: 1.26.0 Depends: R (>= 2.10), R2HTML (>= 1.5), affy (>= 1.23.4), minpack.lm (>= 1.0-5), Biobase (>= 2.5.5) License: GPL-2 MD5sum: a6a87444b0d5959914ccb64cf43c30fd NeedsCompilation: no Title: Hidden Variable Dynamic Modeling Description: A R implementation of HVDM (Genome Biol 2006, V7(3) R25) biocViews: Microarray, GraphsAndNetworks, Transcription, Classification, NetworkInference Author: Martino Barenco Maintainer: Martino Barenco source.ver: src/contrib/rHVDM_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rHVDM_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rHVDM_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rHVDM_1.26.0.tgz vignettes: vignettes/rHVDM/inst/doc/rHVDM.pdf vignetteTitles: rHVDM primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rHVDM/inst/doc/rHVDM.R Package: Ringo Version: 1.24.0 Depends: methods, Biobase (>= 1.14.1), RColorBrewer, limma, Matrix, grid Imports: BiocGenerics (>= 0.1.11), genefilter, limma, vsn, stats4 Suggests: rtracklayer (>= 1.3.1), mclust, topGO (>= 1.15.0) License: Artistic-2.0 Archs: i386, x64 MD5sum: 2d573eaa88f26eff2a4912004a334880 NeedsCompilation: yes Title: R Investigation of ChIP-chip Oligoarrays Description: The package Ringo facilitates the primary analysis of ChIP-chip data. The main functionalities of the package are data read-in, quality assessment, data visualisation and identification of genomic regions showing enrichment in ChIP-chip. The package has functions to deal with two-color oligonucleotide microarrays from NimbleGen used in ChIP-chip projects, but also contains more general functions for ChIP-chip data analysis, given that the data is supplied as RGList (raw) or ExpressionSet (pre- processed). The package employs functions from various other packages of the Bioconductor project and provides additional ChIP-chip-specific and NimbleGen-specific functionalities. biocViews: Microarray,TwoChannel,DataImport,QualityControl,Preprocessing Author: Joern Toedling, Oleg Sklyar, Tammo Krueger, Matt Ritchie, Wolfgang Huber Maintainer: J. Toedling source.ver: src/contrib/Ringo_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Ringo_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Ringo_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Ringo_1.24.0.tgz vignettes: vignettes/Ringo/inst/doc/Ringo.pdf vignetteTitles: R Investigation of NimbleGen Oligoarrays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Ringo/inst/doc/Ringo.R dependsOnMe: Starr importsMe: Repitools suggestsMe: Repitools Package: RIPSeeker Version: 1.0.0 Depends: R (>= 2.15), methods, IRanges, GenomicRanges, rtracklayer, Rsamtools Suggests: biomaRt, ChIPpeakAnno, parallel, GenomicFeatures License: GPL-2 MD5sum: 3bc8f4c63b35939e4f6774a408972a4b NeedsCompilation: no Title: RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments Description: Infer and discriminate RIP peaks from RIP-seq alignments using two-state HMM with negative binomial emission probability. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation. biocViews: HighThroughputSequencing, RIPseq Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/software.html source.ver: src/contrib/RIPSeeker_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RIPSeeker_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RIPSeeker_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RIPSeeker_1.0.0.tgz vignettes: vignettes/RIPSeeker/inst/doc/RIPSeeker.pdf vignetteTitles: RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RIPSeeker/inst/doc/RIPSeeker.R Package: Risa Version: 1.2.2 Depends: R (>= 2.0.9), Biobase (>= 2.4.0), methods, Rcpp (>= 0.9.13), biocViews, affy Imports: xcms Suggests: faahKO (>= 1.2.11) License: LGPL MD5sum: 0a9287809d9ba98a841d4c20e1f8a4fb NeedsCompilation: no Title: Converting experimental metadata from ISA-tab into Bioconductor data structures Description: The Investigation / Study / Assay (ISA) tab-delimited format is a general purpose framework with which to collect and communicate complex metadata (i.e. sample characteristics, technologies used, type of measurements made) from experiments employing a combination of technologies, spanning from traditional approaches to high-throughput techniques. Risa allows to access metadata/data in ISA-Tab format and build Bioconductor data structures. Currently, data generated from microarray, flow cytometry and metabolomics-based (i.e. mass spectrometry) assays are supported. The package is extendable and efforts are undergoing to support metadata associated to proteomics assays. biocViews: Annotation, DataImport, MassSpectrometry Author: Alejandra Gonzalez-Beltran, Audrey Kauffmann, Steffen Neumann, Gabriella Rustici, ISA Team Maintainer: Alejandra Gonzalez-Beltran, ISA Team URL: source.ver: src/contrib/Risa_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/Risa_1.2.2.zip win64.binary.ver: bin/windows64/contrib/2.16/Risa_1.2.2.zip mac.binary.ver: bin/macosx/contrib/2.16/Risa_1.2.2.tgz vignettes: vignettes/Risa/inst/doc/Risa.pdf vignetteTitles: Risa: converts experimental metadata from ISA-tab into Bioconductor data structures hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Risa/inst/doc/Risa.R Package: RLMM Version: 1.22.0 Depends: R (>= 2.1.0) Imports: graphics, grDevices, MASS, stats, utils License: LGPL (>= 2) MD5sum: af62b47b59859ae0c94e6654a4b3ab38 NeedsCompilation: no Title: A Genotype Calling Algorithm for Affymetrix SNP Arrays Description: A classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now. biocViews: Microarray, OneChannel, SNP, GeneticVariability Author: Nusrat Rabbee , Gary Wong Maintainer: Nusrat Rabbee URL: http://www.stat.berkeley.edu/users/nrabbee/RLMM SystemRequirements: Internal files Xba.CQV, Xba.regions (or other regions file) source.ver: src/contrib/RLMM_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RLMM_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RLMM_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RLMM_1.22.0.tgz vignettes: vignettes/RLMM/inst/doc/RLMM.pdf vignetteTitles: RLMM Doc hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RLMM/inst/doc/RLMM.R Package: Rmagpie Version: 1.16.0 Depends: R (>= 2.6.1), Biobase (>= 2.5.5) Imports: Biobase (>= 2.5.5), e1071, graphics, grDevices, kernlab, methods, pamr, stats, utils Suggests: xtable License: GPL (>= 3) MD5sum: 25868797bfad4cbdbe201244edd0efb1 NeedsCompilation: no Title: MicroArray Gene-expression-based Program In Error rate estimation Description: Microarray Classification is designed for both biologists and statisticians. It offers the ability to train a classifier on a labelled microarray dataset and to then use that classifier to predict the class of new observations. A range of modern classifiers are available, including support vector machines (SVMs), nearest shrunken centroids (NSCs)... Advanced methods are provided to estimate the predictive error rate and to report the subset of genes which appear essential in discriminating between classes. biocViews: Microarray, Classification Author: Camille Maumet , with contributions from C. Ambroise J. Zhu Maintainer: Camille Maumet URL: http://www.bioconductor.org/ source.ver: src/contrib/Rmagpie_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rmagpie_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Rmagpie_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Rmagpie_1.16.0.tgz vignettes: vignettes/Rmagpie/inst/doc/Magpie_examples.pdf vignetteTitles: Rmagpie Examples hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rmagpie/inst/doc/Magpie_examples.R Package: RMAPPER Version: 1.10.0 Depends: methods Suggests: RCurl License: Artistic 2.0 MD5sum: 9d9505bf642eabdc23b07ff78e81a365 NeedsCompilation: no Title: R interface to the MAPPER database of transcription factor binding sites Description: The RMAPPER package allows you to retrieve a set of predicted transcription factor binding sites from the MAPPER database (http://genome.ufl.edu/mapper/) through a simple HTTP request. biocViews: Annotation, Genetics Author: VJ Carey Maintainer: Heike Sichtig , Alberto Riva source.ver: src/contrib/RMAPPER_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RMAPPER_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RMAPPER_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RMAPPER_1.10.0.tgz vignettes: vignettes/RMAPPER/inst/doc/readMAPPER.pdf vignetteTitles: Interface to MAPPER TFBS database hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RMAPPER/inst/doc/readMAPPER.R Package: RMassBank Version: 1.2.1 Depends: rcdk,yaml,mzR,methods,rjson Imports: XML,RCurl Suggests: gplots,RMassBankData,xcms License: Artistic-2.0 MD5sum: d4301a0154c6043e189529e44941270d NeedsCompilation: no Title: Workflow to process tandem MS files and build MassBank records Description: Workflow to process tandem MS files and build MassBank records. Functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum cleanup, automated retrieval of compound information from Internet databases, and export to MassBank records. biocViews: Bioinformatics, MassSpectrometry, Metabolomics, Software Author: Michael Stravs, Emma Schymanski Maintainer: Michael Stravs, Emma Schymanski SystemRequirements: OpenBabel source.ver: src/contrib/RMassBank_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/RMassBank_1.2.1.zip win64.binary.ver: bin/windows64/contrib/2.16/RMassBank_1.2.1.zip mac.binary.ver: bin/macosx/contrib/2.16/RMassBank_1.2.1.tgz vignettes: vignettes/RMassBank/inst/doc/RMassBank.pdf vignetteTitles: RMassBank walkthrough hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RMassBank/inst/doc/RMassBank.R Package: rMAT Version: 3.10.0 Depends: R(>= 2.9.0), BiocGenerics (>= 0.1.3), IRanges (>= 1.13.10), Biobase (>= 2.15.1), affxparser Imports: stats, methods, BiocGenerics, IRanges, Biobase, affxparser, stats4 Suggests: GenomeGraphs, rtracklayer License: Artistic-2.0 MD5sum: bf1e198fb0e98f4a41c45acafae2a5e4 NeedsCompilation: yes Title: R implementation from MAT program to normalize and analyze tiling arrays and ChIP-chip data. Description: This package is an R version of the package MAT and contains functions to parse and merge Affymetrix BPMAP and CEL tiling array files (using C++ based Fusion SDK and Bioconductor package affxparser), normalize tiling arrays using sequence specific models, detect enriched regions from ChIP-chip experiments. Note: users should have GSL and GenomeGraphs installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. Snow Leopard users can take advantage of increase speed with Grand Central Dispatch! biocViews: Microarray, Preprocessing Author: Charles Cheung and Arnaud Droit and Raphael Gottardo Maintainer: Arnaud Droit and Raphael Gottardo URL: http://www.rglab.org source.ver: src/contrib/rMAT_3.10.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/rMAT_3.10.0.tgz vignettes: vignettes/rMAT/inst/doc/rMAT.pdf vignetteTitles: The rMAT users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rMAT/inst/doc/rMAT.R Package: RmiR Version: 1.16.0 Depends: R (>= 2.7.0), RmiR.Hs.miRNA, RSVGTipsDevice Imports: DBI, methods, stats Suggests: hgug4112a.db,org.Hs.eg.db License: Artistic-2.0 MD5sum: 59e66158ee7dd513c0dc744102e3671b NeedsCompilation: no Title: Package to work with miRNAs and miRNA targets with R Description: Useful functions to merge microRNA and respective targets using differents databases biocViews: Software,GeneExpression,Microarray,TimeCourse,Visualization Author: Francesco Favero Maintainer: Francesco Favero source.ver: src/contrib/RmiR_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RmiR_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RmiR_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RmiR_1.16.0.tgz vignettes: vignettes/RmiR/inst/doc/RmiR.pdf vignetteTitles: RmiR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RmiR/inst/doc/RmiR.R suggestsMe: oneChannelGUI Package: RNAinteract Version: 1.8.0 Depends: R (>= 2.12.0), abind, locfit, Biobase Imports: RColorBrewer, ICS, ICSNP, cellHTS2, geneplotter, gplots, grid, hwriter, lattice, latticeExtra, limma, methods, splots (>= 1.13.12) License: Artistic-2.0 MD5sum: 734dfa9930afad9206f2083c606dc184 NeedsCompilation: no Title: Estimate Pairwise Interactions from multidimensional features Description: RNAinteract estimates genetic interactions from multi-dimensional read-outs like features extracted from images. The screen is assumed to be performed in multi-well plates or similar designs. Starting from a list of features (e.g. cell number, area, fluorescence intensity) per well, genetic interactions are estimated. The packages provides functions for reporting interacting gene pairs, plotting heatmaps and double RNAi plots. An HTML report can be written for quality control and analysis. biocViews: CellBasedAssays, QualityControl, Preprocessing, Visualization Author: Bernd Fischer Maintainer: Bernd Fischer source.ver: src/contrib/RNAinteract_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RNAinteract_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RNAinteract_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RNAinteract_1.8.0.tgz vignettes: vignettes/RNAinteract/inst/doc/RNAinteract.pdf vignetteTitles: RNAinteract hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RNAinteract/inst/doc/RNAinteract.R Package: RNAither Version: 2.8.0 Depends: R (>= 2.10), topGO, RankProd, prada Imports: geneplotter, limma, biomaRt, car, splots, methods License: Artistic-2.0 MD5sum: 1a9819b5ae13bc435b24e3a3557e5878 NeedsCompilation: no Title: Statistical analysis of high-throughput RNAi screens Description: RNAither analyzes cell-based RNAi screens, and includes quality assessment, customizable normalization and statistical tests, leading to lists of significant genes and biological processes. biocViews: CellBasedAssays, QualityControl, Preprocessing, Visualization, Bioinformatics, Annotation, GO Author: Nora Rieber and Lars Kaderali, University of Heidelberg, Viroquant Research Group Modeling, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Maintainer: Nora Rieber source.ver: src/contrib/RNAither_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RNAither_2.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RNAither_2.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RNAither_2.8.0.tgz vignettes: vignettes/RNAither/inst/doc/vignetteRNAither.pdf vignetteTitles: RNAither,, an automated pipeline for the statistical analysis of high-throughput RNAi screens hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RNAither/inst/doc/vignetteRNAither.R Package: rnaSeqMap Version: 2.14.0 Depends: R (>= 2.11.0), methods, xmapcore, Biobase, Rsamtools Imports: GenomicRanges, IRanges, edgeR, DESeq, DBI, RMySQL (>= 0.6-0) License: GPL-2 MD5sum: 4f2274328c2c31e318894a59f16f7d69 NeedsCompilation: yes Title: rnaSeq secondary analyses Description: The rnaSeqMap library provides classes and functions to analyze the RNA-sequencing data using the coverage profiles in multiple samples at a time biocViews: Annotation, Bioinformatics, ReportWriting, Transcription, GeneExpression, DifferentialExpression, HighThroughputSequencing, RNAseq, SAGE, Visualization Author: Anna Lesniewska ; Michal Okoniewski Maintainer: Michal Okoniewski source.ver: src/contrib/rnaSeqMap_2.14.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/rnaSeqMap_2.14.0.tgz vignettes: vignettes/rnaSeqMap/inst/doc/rnaSeqMap.pdf vignetteTitles: rnaSeqMap primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rnaSeqMap/inst/doc/rnaSeqMap.R Package: RNASeqPower Version: 1.0.0 License: LGPL (>=2) MD5sum: 26a679825c7707620f29c7e32f4c2800 NeedsCompilation: no Title: Sample size for RNAseq studies Description: RNA-seq, sample size Author: Terry M Therneau [aut, cre], Hart Stephen [ctb] Maintainer: Terry M Therneau source.ver: src/contrib/RNASeqPower_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RNASeqPower_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RNASeqPower_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RNASeqPower_1.0.0.tgz vignettes: vignettes/RNASeqPower/inst/doc/samplesize.pdf vignetteTitles: RNAseq samplesize hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RNASeqPower/inst/doc/samplesize.R Package: ROC Version: 1.36.0 Depends: R (>= 1.9.0), utils, methods Suggests: Biobase License: Artistic-2.0 Archs: i386, x64 MD5sum: a924244bd8b68ecd020176af7ee05c20 NeedsCompilation: yes Title: utilities for ROC, with uarray focus Description: utilities for ROC, with uarray focus biocViews: Bioinformatics, DifferentialExpression Author: Vince Carey , Henning Redestig for C++ language enhancements Maintainer: Vince Carey URL: http://www.bioconductor.org source.ver: src/contrib/ROC_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ROC_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ROC_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ROC_1.36.0.tgz vignettes: vignettes/ROC/inst/doc/ROCnotes.pdf vignetteTitles: ROC notes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ROC/inst/doc/ROCnotes.R dependsOnMe: wateRmelon importsMe: clst suggestsMe: genefilter, MCRestimate Package: Rolexa Version: 1.16.0 Depends: R (>= 2.9.0), graphics, grDevices, methods, ShortRead Imports: mclust, Biostrings, graphics, grDevices, IRanges, methods, ShortRead, stats Enhances: fork License: GPL-2 MD5sum: c766c2e275155a61a2eea9257152a5fb NeedsCompilation: no Title: Statistical analysis of Solexa sequencing data Description: Provides probabilistic base calling, quality checks and diagnostic plots for Solexa sequencing data biocViews: Sequencing, DataImport, Preprocessing, QualityControl Author: Jacques Rougemont, Arnaud Amzallag, Christian Iseli, Laurent Farinelli, Ioannis Xenarios, Felix Naef Maintainer: Jacques Rougemont source.ver: src/contrib/Rolexa_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rolexa_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Rolexa_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Rolexa_1.16.0.tgz vignettes: vignettes/Rolexa/inst/doc/Rolexa-vignette.pdf vignetteTitles: Rolexa hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rolexa/inst/doc/Rolexa-vignette.R Package: rols Version: 1.2.2 Depends: methods Imports: XML, XMLSchema (>= 0.6.0), SSOAP (>= 0.8.0), Biobase Suggests: xtable, GO.db, knitr (>= 1.1.0) License: GPL-2 MD5sum: 49be871ed10921a5ca25deadb5d95abd NeedsCompilation: no Title: An R interface to the Ontology Lookup Service Description: This package allows to query EBI's Ontology Lookup Service (OLS) using Simple Object Access Protocol (SOAP). biocViews: Software, Annotation, MassSpectrometry, GO Author: Laurent Gatto Maintainer: Laurent Gatto URL: http://lgatto.github.com/rols/ VignetteBuilder: knitr source.ver: src/contrib/rols_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/rols_1.2.2.zip win64.binary.ver: bin/windows64/contrib/2.16/rols_1.2.2.zip mac.binary.ver: bin/macosx/contrib/2.16/rols_1.2.2.tgz vignettes: vignettes/rols/inst/doc/rols.pdf vignetteTitles: The rols interface to the Ontology Lookup Service hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rols/inst/doc/rols.R suggestsMe: MSnbase Package: ROntoTools Version: 1.0.0 Depends: methods, graph, boot, KEGGREST, KEGGgraph, Rgraphviz Suggests: RUnit, BiocGenerics License: GPL (>= 3) MD5sum: effb7140746080b8ee61745139f7f706 NeedsCompilation: no Title: R Onto-Tools suite Description: Suite of tools for functional analysis biocViews: NetworkAnalysis, Microarray, GraphsAndNetworks Author: Calin Voichita and Sorin Draghici Maintainer: Calin Voichita source.ver: src/contrib/ROntoTools_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ROntoTools_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ROntoTools_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ROntoTools_1.0.0.tgz vignettes: vignettes/ROntoTools/inst/doc/rontotools.pdf vignetteTitles: ROntoTools hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ROntoTools/inst/doc/rontotools.R Package: RPA Version: 1.16.0 Depends: R (>= 2.15.0), affy, affydata, methods, parallel License: FreeBSD MD5sum: a8d221133cb19c52fa5e41289e11cbfd NeedsCompilation: no Title: RPA: Robust Probabilistic Averaging for probe-level analysis Description: Probabilistic analysis of probe reliability and differential gene expression on short oligonucleotide arrays. Lahti et al. "Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays", TCBB/IEEE, 2011. http://doi.ieeecomputersociety.org/10.1109/TCBB.2009.38 biocViews: GeneExpression, Microarray, Preprocessing, QualityControl Author: Leo Lahti Maintainer: Leo Lahti source.ver: src/contrib/RPA_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RPA_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RPA_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RPA_1.16.0.tgz vignettes: vignettes/RPA/inst/doc/RPA.pdf vignetteTitles: RPA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RPA/inst/doc/RPA.R Package: RpsiXML Version: 2.2.0 Depends: methods, annotate (>= 1.21.0), graph (>= 1.21.0), Biobase, RBGL (>= 1.17.0), XML (>= 2.4.0), hypergraph (>= 1.15.2), AnnotationDbi Suggests: org.Hs.eg.db, org.Mm.eg.db, org.Dm.eg.db, org.Rn.eg.db, org.Sc.sgd.db,hom.Hs.inp.db, hom.Mm.inp.db, hom.Dm.inp.db, hom.Rn.inp.db, hom.Sc.inp.db,Rgraphviz, ppiStats, ScISI License: LGPL-3 MD5sum: 53a8ca131e9aadd8d083616cd750013d NeedsCompilation: no Title: R interface to PSI-MI 2.5 files Description: Queries, data structure and interface to visualization of interaction datasets. This package inplements the PSI-MI 2.5 standard and supports up to now 8 databases. Further databases supporting PSI-MI 2.5 standard will be added continuously. biocViews: Infrastructure, Proteomics Author: Jitao David Zhang, Stefan Wiemann, Marc Carlson, with contributions from Tony Chiang Maintainer: Jitao David Zhang URL: http://www.bioconductor.org source.ver: src/contrib/RpsiXML_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RpsiXML_2.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RpsiXML_2.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RpsiXML_2.2.0.tgz vignettes: vignettes/RpsiXML/inst/doc/RpsiXMLApp.pdf, vignettes/RpsiXML/inst/doc/RpsiXML.pdf vignetteTitles: Application Examples of RpsiXML package, Reading PSI-25 XML files hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RpsiXML/inst/doc/RpsiXMLApp.R, vignettes/RpsiXML/inst/doc/RpsiXML.R dependsOnMe: ScISI importsMe: ScISI Package: rqubic Version: 1.6.0 Depends: methods, Biobase, biclust Imports: Biobase, biclust Suggests: RColorBrewer License: GPL-2 Archs: i386, x64 MD5sum: db7b2415b533b6bb1afbb6dd9a9c3082 NeedsCompilation: yes Title: Qualitative biclustering algorithm for expression data analysis in R Description: This package implements the QUBIC algorithm introduced by Li et al. for the qualitative biclustering with gene expression data. biocViews: Microarray, Clustering Author: Jitao David Zhang, with inputs from Laura Badi and Martin Ebeling Maintainer: Jitao David Zhang source.ver: src/contrib/rqubic_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/rqubic_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/rqubic_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/rqubic_1.6.0.tgz vignettes: vignettes/rqubic/inst/doc/rqubic.pdf vignetteTitles: Qualitative Biclustering with Bioconductor Package rqubic hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rqubic/inst/doc/rqubic.R Package: Rsamtools Version: 1.12.4 Depends: methods, IRanges (>= 1.15.35), GenomicRanges (>= 1.11.38), Biostrings (>= 2.25.6) Imports: methods, utils, IRanges, GenomicRanges, Biostrings, zlibbioc, bitops, BiocGenerics (>= 0.1.3) LinkingTo: Biostrings, IRanges Suggests: ShortRead (>= 1.13.19), GenomicFeatures, TxDb.Dmelanogaster.UCSC.dm3.ensGene, KEGG.db, pasillaBamSubset, RUnit, TxDb.Hsapiens.UCSC.hg18.knownGene License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: 75189a4203fb3eb9bd8cda03f3e8c523 NeedsCompilation: yes Title: Binary alignment (BAM), variant call (BCF), or tabix file import Description: This package provides an interface to the 'samtools', 'bcftools', and 'tabix' utilities (see 'LICENCE') for manipulating SAM (Sequence Alignment / Map), binary variant call (BCF) and compressed indexed tab-delimited (tabix) files. biocViews: DataImport, Sequencing, HighThroughputSequencing Author: Martin Morgan, Herv\'e Pag\`es Maintainer: Bioconductor Package Maintainer URL: http://bioconductor.org/packages/release/bioc/html/Rsamtools.html source.ver: src/contrib/Rsamtools_1.12.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rsamtools_1.12.4.zip win64.binary.ver: bin/windows64/contrib/2.16/Rsamtools_1.12.4.zip mac.binary.ver: bin/macosx/contrib/2.16/Rsamtools_1.12.4.tgz vignettes: vignettes/Rsamtools/inst/doc/Rsamtools-Overview.pdf, vignettes/Rsamtools/inst/doc/Rsamtools-UsingCLibraries.pdf vignetteTitles: An introduction to Rsamtools, Using samtools C libraries hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/Rsamtools/inst/doc/Rsamtools-Overview.R, vignettes/Rsamtools/inst/doc/Rsamtools-UsingCLibraries.R dependsOnMe: ArrayExpressHTS, BitSeq, casper, chimera, deepSNV, easyRNASeq, EDASeq, exomeCopy, GGtools, girafe, oneChannelGUI, prebs, qrqc, Rcade, ReQON, RIPSeeker, rnaSeqMap, ShortRead, TEQC, VariantAnnotation importsMe: annmap, ArrayExpressHTS, biovizBase, CAGEr, deepSNV, DEXSeq, FunciSNP, ggbio, gmapR, HTSeqGenie, MEDIPS, PICS, QuasR, R453Plus1Toolbox, rtracklayer, ShortRead, VariantAnnotation, VariantTools suggestsMe: AnnotationHub, biomvRCNS, DiffBind, GenomicFeatures, GenomicRanges, QuasR, R453Plus1Toolbox, seqbias, SplicingGraphs, Streamer Package: rsbml Version: 2.18.1 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), methods, utils Imports: BiocGenerics, graph, utils License: Artistic-2.0 Archs: i386, x64 MD5sum: c148f3e979a189d60320672b3eb56515 NeedsCompilation: yes Title: R support for SBML, using libsbml Description: Links R to libsbml for SBML parsing, validating output, provides an S4 SBML DOM, converts SBML to R graph objects. Optionally links to the SBML ODE Solver Library (SOSLib) for simulating models. biocViews: GraphsAndNetworks, Pathways, NetworkAnalysis Author: Michael Lawrence Maintainer: Michael Lawrence URL: http://www.sbml.org SystemRequirements: libsbml (>=3.0.3) source.ver: src/contrib/rsbml_2.18.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/rsbml_2.18.1.zip win64.binary.ver: bin/windows64/contrib/2.16/rsbml_2.18.1.zip mac.binary.ver: bin/macosx/contrib/2.16/rsbml_2.18.1.tgz vignettes: vignettes/rsbml/inst/doc/quick-start.pdf vignetteTitles: Quick start for rsbml hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rsbml/inst/doc/quick-start.R suggestsMe: piano Package: rSFFreader Version: 0.8.0 Depends: R (>= 2.13.0), Biostrings (>= 2.25.12), IRanges(>= 1.15.42), GenomicRanges, ShortRead(>= 1.15.9), xtable, methods Imports: methods, Biostrings, IRanges, ShortRead, GenomicRanges, Biobase LinkingTo: Biostrings, IRanges License: Artistic-2.0 MD5sum: fc158648a57466a865b3cf5bd19a26bb NeedsCompilation: yes Title: rSFFreader reads in sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers Description: rSFFreader reads sequence, qualities and clip point values from sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers. The plan is to also write out sff files and to read in flowgrams with some utils biocViews: DataImport, Sequencing, HighThroughputSequencing Author: Matt Settles , Sam Hunter, Brice Sarver, Ilia Zhbannikov, Kyu-Chul Cho Maintainer: Matt Settles source.ver: src/contrib/rSFFreader_0.8.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/rSFFreader_0.8.0.tgz vignettes: vignettes/rSFFreader/inst/doc/rSFFreader.pdf vignetteTitles: An introduction to rSFFreader hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rSFFreader/inst/doc/rSFFreader.R Package: Rsubread Version: 1.10.5 License: GPL-3 MD5sum: 6638cc85446ad0aa0f26aedbcc341fbe NeedsCompilation: yes Title: Rsubread: an R package for the alignment, summarization and analyses of next-generation sequencing data Description: This R package provides facilities for processing the read data generated by the next-gen sequencing technologies. These facilities include quality assessment, read alignment, read summarization, exon-exon junction detection, absolute expression calling and SNP discovery. This package can be used to process both short and long reads. It supports major sequencing platforms such as Illumina GA/HiSeq, Roche 454, ABI SOLiD and Ion Torrent. biocViews: Sequencing, HighThroughputSequencing Author: Wei Shi and Yang Liao with contributions from Jenny Zhiyin Dai and Timothy Triche, Jr. Maintainer: Wei Shi URL: http://bioconductor.org/packages/release/bioc/html/Rsubread.html source.ver: src/contrib/Rsubread_1.10.5.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/Rsubread_1.10.5.tgz vignettes: vignettes/Rsubread/inst/doc/Rsubread.pdf, vignettes/Rsubread/inst/doc/SubreadUsersGuide.pdf vignetteTitles: Rsubread Vignette, SubreadUsersGuide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rsubread/inst/doc/Rsubread.R Package: RSVSim Version: 1.0.2 Depends: R (>= 3.0.0), Biostrings, GenomicRanges Imports: methods, IRanges, ShortRead Suggests: BSgenome.Hsapiens.UCSC.hg19, MASS, rtracklayer License: LGPL-3 MD5sum: 3c16d74298babe845f7c94300f56ebba NeedsCompilation: no Title: RSVSim: an R/Bioconductor package for the simulation of structural variations Description: RSVSim is a package for the simulation of deletions, insertions, inversion, tandem-duplications and translocations of various sizes in any genome available as FASTA-file or BSgenome data package. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates. biocViews: Bioinformatics,HighThroughputSequencing,HighThroughputSequencingData Author: Christoph Bartenhagen Maintainer: Christoph Bartenhagen source.ver: src/contrib/RSVSim_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/RSVSim_1.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/RSVSim_1.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/RSVSim_1.0.2.tgz vignettes: vignettes/RSVSim/inst/doc/vignette.pdf vignetteTitles: RSVSim: an R/Bioconductor package for the simulation of structural variations hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RSVSim/inst/doc/vignette.R Package: rTANDEM Version: 1.0.1 Depends: XML, Rcpp, data.table (>= 1.8.8) Imports: methods LinkingTo: Rcpp Suggests: biomaRt License: Artistic-1.0 | file LICENSE Archs: i386, x64 MD5sum: c3f4adebda13fed78907393eaaf3561f NeedsCompilation: yes Title: Encapsulate X!Tandem in R. Description: This package encapsulate X!Tandem in R. In its most basic functionality, this package allows to call tandem(input) from R, just as tandem.exe /path/to/input.xml would be used to run X!Tandem from the command line. Classes are also provided for taxonomy and parameters objects and methods are provided to convert xml files to R objects and vice versa. This package is the first step in an attempt to provide a reliable worflow for proteomics analysis in R. biocViews: MassSpectrometry, Proteomics Author: Frederic Fournier , Charles Joly Beauparlant , Rene Paradis , Arnaud Droit Maintainer: Frederic Fournier SystemRequirements: rTANDEM uses expat and pthread libraries. See the README file for details. source.ver: src/contrib/rTANDEM_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/rTANDEM_1.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/rTANDEM_1.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/rTANDEM_1.0.1.tgz vignettes: vignettes/rTANDEM/inst/doc/rTANDEM.pdf vignetteTitles: The rTANDEM users guide hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/rTANDEM/inst/doc/rTANDEM.R Package: RTCA Version: 1.12.0 Depends: methods,stats,graphics,Biobase,RColorBrewer, gtools Suggests: xtable License: LGPL-3 MD5sum: 5d183c02cba8610897cacd4b1c9db76f NeedsCompilation: no Title: Open-source toolkit to analyse data from xCELLigence System (RTCA) Description: Import, analyze and visualize data from Roche(R) xCELLigence RTCA systems. The package imports real-time cell electrical impedance data into R. As an alternative to commercial software shipped along the system, the Bioconductor package RTCA provides several unique transformation (normalization) strategies and various visualization tools. biocViews: CellBasedAssays, Infrastructure, Visualization, TimeCourse Author: Jitao David Zhang Maintainer: Jitao David Zhang URL: http://code.google.com/p/xcelligence/, http://www.xcelligence.roche.com/, http://www.nextbiomotif.com/Home/scientific-programming source.ver: src/contrib/RTCA_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RTCA_1.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RTCA_1.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RTCA_1.12.0.tgz vignettes: vignettes/RTCA/inst/doc/aboutRTCA.pdf, vignettes/RTCA/inst/doc/RTCAtransformation.pdf vignetteTitles: Introduction to Data Analysis of the Roche xCELLigence System with RTCA Package, RTCAtransformation: Discussion of transformation methods of RTCA data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RTCA/inst/doc/aboutRTCA.R, vignettes/RTCA/inst/doc/RTCAtransformation.R Package: RTopper Version: 1.6.0 Depends: R (>= 2.11.0), Biobase Imports: limma, multtest Suggests: limma, org.Hs.eg.db, KEGG.db, GO.db License: GPL (>= 3) MD5sum: 723bce1fb0fa7eac6ae02ed8e2a9d620 NeedsCompilation: no Title: This package is designed to perform Gene Set Analysis across multiple genomic platforms Description: the RTopper package is designed to perform and integrate gene set enrichment results across multiple genomic platforms. biocViews: Microarray Author: Luigi Marchionni , Svitlana Tyekucheva Maintainer: Luigi Marchionni source.ver: src/contrib/RTopper_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/RTopper_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/RTopper_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/RTopper_1.6.0.tgz vignettes: vignettes/RTopper/inst/doc/RTopper.pdf vignetteTitles: RTopper user's manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RTopper/inst/doc/RTopper.R Package: rtracklayer Version: 1.20.4 Depends: R (>= 2.10), methods, GenomicRanges (>= 1.11.12) Imports: XML (>= 1.98-0), BiocGenerics (>= 0.1.0), IRanges (>= 1.15.37), GenomicRanges, Biostrings (>= 2.25.6), BSgenome (>= 1.23.1), zlibbioc, RCurl (>= 1.4-2), Rsamtools (>= 1.7.3) LinkingTo: IRanges Suggests: humanStemCell, microRNA (>= 1.1.1), genefilter, limma, org.Hs.eg.db, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, hgu133plus2.db License: Artistic-2.0 Archs: i386, x64 MD5sum: e584d864bcb943603b8fe07f7f9142f5 NeedsCompilation: yes Title: R interface to genome browsers and their annotation tracks Description: Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport. biocViews: Annotation,Visualization,DataImport Author: Michael Lawrence, Vince Carey, Robert Gentleman Maintainer: Michael Lawrence source.ver: src/contrib/rtracklayer_1.20.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/rtracklayer_1.20.4.zip win64.binary.ver: bin/windows64/contrib/2.16/rtracklayer_1.20.4.zip mac.binary.ver: bin/macosx/contrib/2.16/rtracklayer_1.20.4.tgz vignettes: vignettes/rtracklayer/inst/doc/rtracklayer.pdf vignetteTitles: rtracklayer hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rtracklayer/inst/doc/rtracklayer.R dependsOnMe: cummeRbund, HTSeqGenie, MethylSeekR, RIPSeeker importsMe: BiSeq, CAGEr, ChromHeatMap, GenomicFeatures, ggbio, gmapR, Gviz, HiTC, HTSeqGenie, MEDIPS, methyAnalysis, MotifDb, R453Plus1Toolbox, VariantTools suggestsMe: biovizBase, GenomicFeatures, GenomicRanges, goseq, Gviz, gwascat, HiTC, methylumi, MotIV, NarrowPeaks, oneChannelGUI, PICS, PING, QuasR, R453Plus1Toolbox, Repitools, Ringo, rMAT, RSVSim, triplex, TSSi Package: Rtreemix Version: 1.22.0 Depends: R (>= 2.5.0), methods, graph, Biobase Imports: methods, graph, Biobase, Hmisc Suggests: Rgraphviz License: LGPL Archs: i386, x64 MD5sum: a2b967b6c7d80a552f4a4e68db76554b NeedsCompilation: yes Title: Rtreemix: Mutagenetic trees mixture models. Description: Rtreemix is a package that offers an environment for estimating the mutagenetic trees mixture models from cross-sectional data and using them for various predictions. It includes functions for fitting the trees mixture models, likelihood computations, model comparisons, waiting time estimations, stability analysis, etc. biocViews: Bioinformatics Author: Jasmina Bogojeska Maintainer: Jasmina Bogojeska source.ver: src/contrib/Rtreemix_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Rtreemix_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Rtreemix_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Rtreemix_1.22.0.tgz vignettes: vignettes/Rtreemix/inst/doc/ClassDiagram.pdf, vignettes/Rtreemix/inst/doc/ExtendedVignette.pdf, vignettes/Rtreemix/inst/doc/Rtreemix.pdf, vignettes/Rtreemix/inst/doc/topologies.pdf vignetteTitles: ClassDiagram.pdf, ExtendedVignette.pdf, Rtreemix, topologies.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rtreemix/inst/doc/Rtreemix.R Package: RWebServices Version: 1.24.0 Depends: SJava (>= 0.85), TypeInfo, methods, tools (>= 2.10.0), R (>= 2.5.0) Imports: RCurl, SJava License: file LICENSE License_restricts_use: no MD5sum: 64289f265da38ca350b304be9f745ca8 NeedsCompilation: yes Title: Expose R functions as web services through Java/Axis/Apache Description: This package provides mechanisms for automatic function prototyping and exposure of R functionality in a web services environment. biocViews: Infrastructure Author: Nianhua Li, MT Morgan Maintainer: Martin Morgan source.ver: src/contrib/RWebServices_1.24.0.tar.gz vignettes: vignettes/RWebServices/inst/doc/EnablingPackages.pdf, vignettes/RWebServices/inst/doc/InstallingAndTesting.pdf, vignettes/RWebServices/inst/doc/LessonsLearned.pdf, vignettes/RWebServices/inst/doc/RelatedWork.pdf, vignettes/RWebServices/inst/doc/RToJava.pdf vignetteTitles: Enabling packages as web services, Installing and testing RWebServices and enabled packages, Lessons learned exposing web services, RelatedWork, From R to Java hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RWebServices/inst/doc/EnablingPackages.R, vignettes/RWebServices/inst/doc/InstallingAndTesting.R, vignettes/RWebServices/inst/doc/LessonsLearned.R, vignettes/RWebServices/inst/doc/RelatedWork.R, vignettes/RWebServices/inst/doc/RToJava.R Package: safe Version: 3.0.0 Depends: R (>= 2.4.0), AnnotationDbi, Biobase, methods, SparseM Suggests: GO.db, KEGG.db, PFAM.db, hgu133a.db, breastCancerUPP, survival, foreach, doRNG, Rgraphviz, GOstats License: GPL (>= 2) MD5sum: 2dcf887a626a5b8ad318d92a8247892f NeedsCompilation: no Title: Significance Analysis of Function and Expression Description: SAFE is a resampling-based method for testing functional categories in gene expression experiments. SAFE can be applied to 2-sample and multi-class comparisons, or simple linear regressions. Other experimental designs can also be accommodated through user-defined functions. biocViews: GeneExpression, FunctionalAnnotation Author: William T. Barry Maintainer: William T. Barry source.ver: src/contrib/safe_3.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/safe_3.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/safe_3.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/safe_3.0.0.tgz vignettes: vignettes/safe/inst/doc/SAFEmanual3.pdf vignetteTitles: SAFE manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/safe/inst/doc/SAFEmanual2.R, vignettes/safe/inst/doc/SAFEmanual3.R Package: sagenhaft Version: 1.30.0 Depends: R (>= 2.10), SparseM (>= 0.73), methods Imports: graphics, methods, SparseM, stats, utils License: GPL (>= 2) MD5sum: 269c3367d6278d797876a1d76ce684ac NeedsCompilation: no Title: Collection of functions for reading and comparing SAGE libraries Description: This package implements several functions useful for analysis of gene expression data by sequencing tags as done in SAGE (Serial Analysis of Gene Expressen) data, i.e. extraction of a SAGE library from sequence files, sequence error correction, library comparison. Sequencing error correction is implementing using an Expectation Maximization Algorithm based on a Mixture Model of tag counts. biocViews: SAGE Author: Tim Beissbarth , with contributions from Gordon Smyth and Lavinia Hyde . Maintainer: Tim Beissbarth URL: http://tagcalling.mbgproject.org source.ver: src/contrib/sagenhaft_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/sagenhaft_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/sagenhaft_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/sagenhaft_1.30.0.tgz vignettes: vignettes/sagenhaft/inst/doc/SAGEnhaft.pdf vignetteTitles: SAGEnhaft hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sagenhaft/inst/doc/SAGEnhaft.R Package: SAGx Version: 1.34.0 Depends: R (>= 2.5.0), stats, multtest, methods Imports: Biobase, stats4 Suggests: KEGG.db, hu6800.db, MASS License: GPL-3 Archs: i386, x64 MD5sum: 75797b42c0791449559520974bc4d512 NeedsCompilation: yes Title: Statistical Analysis of the GeneChip Description: A package for retrieval, preparation and analysis of data from the Affymetrix GeneChip. In particular the issue of identifying differentially expressed genes is addressed. biocViews: Microarray, OneChannel, Preprocessing, DataImport, Bioinformatics, DifferentialExpression, Clustering, MultipleComparisons Author: Per Broberg Maintainer: Per Broberg, URL: http://home.swipnet.se/pibroberg/expression_hemsida1.html source.ver: src/contrib/SAGx_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SAGx_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SAGx_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SAGx_1.34.0.tgz vignettes: vignettes/SAGx/inst/doc/samroc-ex.pdf vignetteTitles: samroc - example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SAGx/inst/doc/samroc-ex.R Package: SamSPECTRAL Version: 1.14.1 Depends: R (>= 2.10) Imports: methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 54f8eb36d4cc0d32395f017b9ded4ec4 NeedsCompilation: yes Title: Identifies cell population in flow cytometry data. Description: Samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting "connected components" estimate biological cell populations in the data sample. For instructions on manual installation, refer to the PDF file provided in the following documentation. biocViews: Bioinformatics, FlowCytometry, CellBiology, Clustering, Cancer, FlowCytData, StemCells, HIV Author: Habil Zare and Parisa Shooshtari Maintainer: Habil Zare source.ver: src/contrib/SamSPECTRAL_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/SamSPECTRAL_1.14.1.zip win64.binary.ver: bin/windows64/contrib/2.16/SamSPECTRAL_1.14.1.zip mac.binary.ver: bin/macosx/contrib/2.16/SamSPECTRAL_1.14.1.tgz vignettes: vignettes/SamSPECTRAL/inst/doc/Clustering_by_SamSPECTRAL.pdf vignetteTitles: A modified spectral clustering method for clustering Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SamSPECTRAL/inst/doc/Clustering_by_SamSPECTRAL.R Package: SANTA Version: 1.0.0 Depends: R (>= 2.14), igraph, snow Imports: msm Suggests: RUnit, BiocGenerics, org.Sc.sgd.db License: Artistic-2.0 Archs: i386, x64 MD5sum: f20bad8d0adbb0cfff0389d7a41c0de4 NeedsCompilation: yes Title: Spatial Analysis of Network Associations Description: This package provides methods for measuring the strength of association between a network and a phenotype. It does this by measuring clustering of the phenotype across the network. Vertices can also be individually ranked by their strength of association with high-weight vertices. biocViews: NetworkAnalysis, NetworkEnrichment, Clustering Author: Alex Cornish and Florian Markowetz Maintainer: Alex Cornish source.ver: src/contrib/SANTA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SANTA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SANTA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SANTA_1.0.0.tgz vignettes: vignettes/SANTA/inst/doc/SANTA.pdf vignetteTitles: Using SANTA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SANTA/inst/doc/SANTA.R Package: SBMLR Version: 1.56.0 Depends: XML, deSolve License: GPL-2 MD5sum: c4fa66c9d90c7d31c036cd3217468a7c NeedsCompilation: no Title: SBML-R Interface and Analysis Tools Description: This package contains a systems biology markup language (SBML) interface and biochemical system analysis tools with illustrative examples. biocViews: GraphsAndNetworks, Pathways, NetworkAnalysis Author: Tomas Radivoyevitch Maintainer: Tomas Radivoyevitch URL: http://epbi-radivot.cwru.edu/SBMLR/SBMLR.html source.ver: src/contrib/SBMLR_1.56.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SBMLR_1.56.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SBMLR_1.56.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SBMLR_1.56.0.tgz vignettes: vignettes/SBMLR/inst/doc/BMC.BioInformatics04.pdf, vignettes/SBMLR/inst/doc/manual.pdf, vignettes/SBMLR/inst/doc/quick-start.pdf vignetteTitles: BMC.BioInformatics04.pdf, manual.pdf, Quick intro to SBMLR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SBMLR/inst/doc/quick-start.R Package: SCAN.UPC Version: 2.0.2 Depends: R (>= 2.14.0), Biobase (>= 2.6.0), oligo, Biostrings Imports: utils, methods, MASS, tools Suggests: pd.hg.u95a License: MIT MD5sum: 7bd74f784617839cb1744a0a4ce8c57e NeedsCompilation: no Title: Single-channel array normalization (SCAN) and University Probability of expression Codes (UPC) Description: SCAN is a microarray normalization method to facilitate personalized-medicine workflows. Rather than processing microarray samples as groups, which can introduce biases and present logistical challenges, SCAN normalizes each sample individually by modeling and removing probe- and array-specific background noise using only data from within each array. SCAN can be applied to one-channel (e.g., Affymetrix) or two-channel (e.g., Agilent) microarrays. The Universal Probability of expression Codes (UPC) method is an extension of SCAN that generates probability-of-expression values. These values can be interpreted as the probability that a given genomic feature (e.g., gene, transcript) is expressed above the background in a given sample. The UPC method can be applied to one-channel or two-channel microarrays as well as to RNA-Seq read counts. Because UPC values are represented on the same scale and have an identical interpretation for each platform, they can be used for cross-platform data integration.) biocViews: Software, Microarray, Preprocessing, RNAseq, TwoChannel, OneChannel Author: Stephen R. Piccolo and W. Evan Johnson Maintainer: Stephen R. Piccolo URL: http://bioconductor.org, http://jlab.bu.edu/software/scan-upc source.ver: src/contrib/SCAN.UPC_2.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/SCAN.UPC_2.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/SCAN.UPC_2.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/SCAN.UPC_2.0.2.tgz vignettes: vignettes/SCAN.UPC/inst/doc/SCAN.vignette.pdf vignetteTitles: SCAN - Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/SCAN.UPC/inst/doc/SCAN.vignette.R Package: ScISI Version: 1.32.0 Depends: R (>= 2.10), GO.db, RpsiXML, annotate, apComplex Imports: AnnotationDbi, GO.db, RpsiXML, annotate, methods, org.Sc.sgd.db, utils Suggests: ppiData, xtable License: LGPL MD5sum: eb0ab9dd2430ac2c390c2bacaf8949bc NeedsCompilation: no Title: In Silico Interactome Description: Package to create In Silico Interactomes biocViews: GraphsAndNetworks, Proteomics, NetworkInference Author: Tony Chiang Maintainer: Tony Chiang source.ver: src/contrib/ScISI_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ScISI_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ScISI_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ScISI_1.32.0.tgz vignettes: vignettes/ScISI/inst/doc/vignette.pdf vignetteTitles: ScISI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ScISI/inst/doc/vignette.R dependsOnMe: PCpheno, ppiStats, SLGI importsMe: PCpheno, SLGI suggestsMe: RpsiXML Package: segmentSeq Version: 1.12.1 Depends: R (>= 2.3.0), methods, baySeq (>= 1.11.1), ShortRead, GenomicRanges, IRanges Imports: baySeq, graphics, grDevices, IRanges, methods, utils, GenomicRanges Suggests: snow License: GPL-3 MD5sum: 1a657544db198bfa87ccbed60741649b NeedsCompilation: no Title: Methods for identifying small RNA loci from high-throughput sequencing data Description: High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery. biocViews: Bioinformatics, HighThroughputSequencing, MultipleComparisons Author: Thomas J. Hardcastle Maintainer: Thomas J. Hardcastle source.ver: src/contrib/segmentSeq_1.12.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/segmentSeq_1.12.1.zip win64.binary.ver: bin/windows64/contrib/2.16/segmentSeq_1.12.1.zip mac.binary.ver: bin/macosx/contrib/2.16/segmentSeq_1.12.1.tgz vignettes: vignettes/segmentSeq/inst/doc/segmentSeq.pdf vignetteTitles: segmentSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/segmentSeq/inst/doc/segmentSeq.R Package: SeqArray Version: 1.0.0 Depends: gdsfmt (>= 0.9.12) Suggests: parallel, snow License: GPL-3 Archs: i386, x64 MD5sum: c384072ffb17f4777fe94f2b326e7d24 NeedsCompilation: yes Title: Big Data Management of Genome-wide Sequencing Variants Description: Big data management of genome-wide variants using the CoreArray library, where genotypic data and annotations are stored in an array-oriented manner, offering efficient access of genetic variants using the R language. biocViews: Bioinformatics, Infrastructure Author: Xiuwen Zheng Maintainer: Xiuwen Zheng URL: http://corearray.sourceforge.net/tutorials/SeqArray/ source.ver: src/contrib/SeqArray_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SeqArray_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SeqArray_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SeqArray_1.0.0.tgz vignettes: vignettes/SeqArray/inst/doc/SeqArrayTutorial.pdf vignetteTitles: SeqArray: an R/Bioconductor Package for Big Data Management of Genome-Wide Sequencing Variants hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SeqArray/inst/doc/SeqArrayTutorial.R Package: seqbias Version: 1.8.0 Depends: R (>= 2.13.0), GenomicRanges (>= 0.1.0), Biostrings (>= 2.15.0), methods Imports: zlibbioc LinkingTo: Rsamtools Suggests: Rsamtools, ggplot2 License: LGPL-3 Archs: i386, x64 MD5sum: 7e59deb62e8e8b74df3bac94288853c0 NeedsCompilation: yes Title: Estimation of per-position bias in high-throughput sequencing data Description: This package implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence. biocViews: Sequencing, HighThroughputSequencing Author: Daniel Jones Maintainer: Daniel Jones source.ver: src/contrib/seqbias_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/seqbias_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/seqbias_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/seqbias_1.8.0.tgz vignettes: vignettes/seqbias/inst/doc/overview.pdf vignetteTitles: Assessing and Adjusting for Technical Bias in High Throughput Sequencing Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/seqbias/inst/doc/overview.R dependsOnMe: ReQON Package: SeqGSEA Version: 1.0.2 Depends: Biobase, DESeq, biomaRt, foreach Imports: methods, doParallel License: GPL (>= 3) MD5sum: b5448b11317dd4fa03fbfc71cfc7ab20 NeedsCompilation: no Title: Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing Description: The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively. biocViews: HighThroughputSequencing, RNAseq, GeneSetEnrichment, GeneExpression, DifferentialExpression Author: Xi Wang Maintainer: Xi Wang source.ver: src/contrib/SeqGSEA_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/SeqGSEA_1.0.2.zip win64.binary.ver: bin/windows64/contrib/2.16/SeqGSEA_1.0.2.zip mac.binary.ver: bin/macosx/contrib/2.16/SeqGSEA_1.0.2.tgz vignettes: vignettes/SeqGSEA/inst/doc/SeqGSEA.pdf vignetteTitles: Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SeqGSEA/inst/doc/SeqGSEA.R Package: seqLogo Version: 1.26.0 Depends: methods, grid License: LGPL (>= 2) MD5sum: 03212908bff92c3fd2ac94daa3afda2d NeedsCompilation: no Title: Sequence logos for DNA sequence alignments Description: seqLogo takes the position weight matrix of a DNA sequence motif and plots the corresponding sequence logo as introduced by Schneider and Stephens (1990). biocViews: SequenceMatching Author: Oliver Bembom Maintainer: Oliver Bembom source.ver: src/contrib/seqLogo_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/seqLogo_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/seqLogo_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/seqLogo_1.26.0.tgz vignettes: vignettes/seqLogo/inst/doc/seqLogo.pdf vignetteTitles: Sequence logos for DNA sequence alignments hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/seqLogo/inst/doc/seqLogo.R dependsOnMe: rGADEM importsMe: motifRG, PWMEnrich, rGADEM suggestsMe: BCRANK, MotifDb Package: ShortRead Version: 1.18.0 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.17.18), GenomicRanges (>= 1.11.18), Biostrings (>= 2.25.6), lattice, Rsamtools (>= 1.7.42), latticeExtra Imports: BiocGenerics, IRanges, GenomicRanges, Biostrings, Biobase, hwriter, Rsamtools, zlibbioc, lattice LinkingTo: IRanges, Biostrings Suggests: biomaRt, RUnit, GenomicFeatures, yeastNagalakshmi Enhances: Rmpi, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 448e2057c50c201fcf337abf5556acba NeedsCompilation: yes Title: Classes and methods for high-throughput short-read sequencing data. Description: Base classes, functions, and methods for representation of high-throughput, short-read sequencing data. biocViews: DataImport, Sequencing, HighThroughputSequencing, QualityControl Author: Martin Morgan, Michael Lawrence, Simon Anders Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/ShortRead_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ShortRead_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ShortRead_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ShortRead_1.18.0.tgz vignettes: vignettes/ShortRead/inst/doc/Overview.pdf, vignettes/ShortRead/inst/doc/ShortRead_and_HilbertVis.pdf vignetteTitles: An introduction to ShortRead, ShortRead_and_HilbertVis.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ShortRead/inst/doc/Overview.R dependsOnMe: chipseq, ChIPseqR, easyRNASeq, EDASeq, girafe, HTSeqGenie, nucleR, OTUbase, Rolexa, segmentSeq importsMe: ArrayExpressHTS, chipseq, ChIPseqR, ChIPsim, nucleR, OTUbase, QuasR, R453Plus1Toolbox, Rolexa, rSFFreader, RSVSim suggestsMe: CSAR, DBChIP, Genominator, PICS, PING, R453Plus1Toolbox, Repitools, Rsamtools Package: sigaR Version: 1.4.0 Depends: Biobase, CGHbase, methods, mvtnorm, penalized Imports: corpcor (>= 1.6.2), graphics, igraph, marray, MASS, mvtnorm, quadprog, penalized (>= 0.9-39), snowfall, stats License: GPL (>= 2) MD5sum: 9e1c11d59a592429e700bb5bc7926e85 NeedsCompilation: no Title: statistics for integrative genomics analyses in R Description: Facilites the joint analysis of high-throughput data from multiple molecular levels. Contains functions for manipulation of objects, various analysis types, and some visualization. biocViews: Microarray, Bioinformatics, DifferentialExpression, aCGH, GeneExpression, Pathways Author: Wessel N. van Wieringen Maintainer: Wessel N. van Wieringen URL: http://www.few.vu.nl/~wvanwie source.ver: src/contrib/sigaR_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/sigaR_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/sigaR_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/sigaR_1.4.0.tgz vignettes: vignettes/sigaR/inst/doc/sigaR.pdf, vignettes/sigaR/inst/doc/statisticalUnit.pdf vignetteTitles: sigaR, statisticalUnit.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sigaR/inst/doc/sigaR.R dependsOnMe: HCsnip Package: siggenes Version: 1.34.0 Depends: methods, Biobase, multtest, splines, graphics Imports: stats4 Suggests: affy, annotate, genefilter, KernSmooth, scrime (>= 1.2.5) License: LGPL (>= 2) MD5sum: 5735fdded9ec5b4f39965602257a623f NeedsCompilation: no Title: Multiple testing using SAM and Efron's empirical Bayes approaches Description: Identification of differentially expressed genes and estimation of the False Discovery Rate (FDR) using both the Significance Analysis of Microarrays (SAM) and the Empirical Bayes Analyses of Microarrays (EBAM). biocViews: MultipleComparisons, Microarray, GeneExpression, SNP, ExonArray, DifferentialExpression Author: Holger Schwender Maintainer: Holger Schwender source.ver: src/contrib/siggenes_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/siggenes_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/siggenes_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/siggenes_1.34.0.tgz vignettes: vignettes/siggenes/inst/doc/siggenes.pdf, vignettes/siggenes/inst/doc/siggenesRnews.pdf vignetteTitles: siggenes Manual, siggenesRnews.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/siggenes/inst/doc/siggenes.R htmlDocs: vignettes/siggenes/inst/doc/identify.sam.html, vignettes/siggenes/inst/doc/plot.ebam.html, vignettes/siggenes/inst/doc/plot.finda0.html, vignettes/siggenes/inst/doc/plot.sam.html, vignettes/siggenes/inst/doc/print.ebam.html, vignettes/siggenes/inst/doc/print.finda0.html, vignettes/siggenes/inst/doc/print.sam.html, vignettes/siggenes/inst/doc/summary.ebam.html, vignettes/siggenes/inst/doc/summary.sam.html htmlTitles: "R: SAM specific identify method", "R: EBAM specific plot method", "R: FindA0 specific plot method", "R: SAM specific plot method", "R: EBAM specific print method", "R: FindA0 specific print method", "R: SAM specific print method", "R: EBAM specific summary method", "R: SAM specific summary method" dependsOnMe: KCsmart, oneChannelGUI importsMe: charm, GeneSelector, minfi suggestsMe: GeneSelector, logicFS, XDE Package: sigPathway Version: 1.28.0 Depends: R (>= 2.10) Suggests: hgu133a.db (>= 1.10.0), XML (>= 1.6-3), AnnotationDbi (>= 1.3.12) License: GPL-2 Archs: i386, x64 MD5sum: 17bfc3fc22fea3a7c96ea2812ca74c77 NeedsCompilation: yes Title: Pathway Analysis Description: Conducts pathway analysis by calculating the NT_k and NE_k statistics as described in Tian et al. (2005) biocViews: Bioinformatics, DifferentialExpression, MultipleComparisons Author: Weil Lai (optimized R and C code), Lu Tian and Peter Park (algorithm development and initial R code) Maintainer: Weil Lai URL: http://www.pnas.org/cgi/doi/10.1073/pnas.0506577102, http://www.chip.org/~ppark/Supplements/PNAS05.html source.ver: src/contrib/sigPathway_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/sigPathway_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/sigPathway_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/sigPathway_1.28.0.tgz vignettes: vignettes/sigPathway/inst/doc/sigPathway-vignette.pdf vignetteTitles: sigPathway hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sigPathway/inst/doc/sigPathway-vignette.R Package: SIM Version: 1.30.0 Depends: R (>= 2.4), quantreg Imports: graphics, stats, globaltest, quantsmooth Suggests: biomaRt, RColorBrewer License: GPL (>= 2) Archs: i386, x64 MD5sum: 79465815627592941c23d634e2c9d15c NeedsCompilation: yes Title: Integrated Analysis on two human genomic datasets Description: Finds associations between two human genomic datasets. biocViews: Microarray, Bioinformatics, Visualization Author: Renee X. de Menezes and Judith M. Boer Maintainer: Renee X. de Menezes source.ver: src/contrib/SIM_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SIM_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SIM_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SIM_1.30.0.tgz vignettes: vignettes/SIM/inst/doc/SIM.pdf vignetteTitles: SIM vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SIM/inst/doc/SIM.R Package: simpleaffy Version: 2.36.1 Depends: R (>= 2.0.0), methods, utils, grDevices, graphics, stats, BiocGenerics (>= 0.1.12), Biobase, affy (>= 1.33.6), genefilter, gcrma Imports: methods, utils, grDevices, graphics, stats, BiocGenerics, Biobase, affy, genefilter, gcrma License: GPL (>= 2) Archs: i386, x64 MD5sum: 7960412a29c002f6098e1f8873174629 NeedsCompilation: yes Title: Very simple high level analysis of Affymetrix data Description: Provides high level functions for reading Affy .CEL files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. Makes heavy use of the affy library. Also has some basic scatter plot functions and mechanisms for generating high resolution journal figures... biocViews: Microarray, OneChannel, QualityControl, Preprocessing, Transcription, DataImport, Bioinformatics, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Crispin J Miller Maintainer: Crispin Miller URL: http://www.bioconductor.org, http://bioinformatics.picr.man.ac.uk/simpleaffy/ source.ver: src/contrib/simpleaffy_2.36.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/simpleaffy_2.36.1.zip win64.binary.ver: bin/windows64/contrib/2.16/simpleaffy_2.36.1.zip mac.binary.ver: bin/macosx/contrib/2.16/simpleaffy_2.36.1.tgz vignettes: vignettes/simpleaffy/inst/doc/QCandSimpleaffy.pdf, vignettes/simpleaffy/inst/doc/simpleAffy.pdf vignetteTitles: QCandSimpleaffy.pdf, simpleaffy primer hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/simpleaffy/inst/doc/simpleAffy.R dependsOnMe: yaqcaffy importsMe: affyQCReport, arrayMvout, arrayQualityMetrics suggestsMe: AffyExpress, ArrayTools Package: sizepower Version: 1.30.0 Depends: stats License: LGPL MD5sum: 8d1cec6ed61c1520d141037f19cd8ce9 NeedsCompilation: no Title: Sample Size and Power Calculation in Micorarray Studies Description: This package has been prepared to assist users in computing either a sample size or power value for a microarray experimental study. The user is referred to the cited references for technical background on the methodology underpinning these calculations. This package provides support for five types of sample size and power calculations. These five types can be adapted in various ways to encompass many of the standard designs encountered in practice. biocViews: Microarray, Bioinformatics Author: Weiliang Qiu and Mei-Ling Ting Lee and George Alex Whitmore Maintainer: Weiliang Qiu source.ver: src/contrib/sizepower_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/sizepower_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/sizepower_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/sizepower_1.30.0.tgz vignettes: vignettes/sizepower/inst/doc/sizepower.pdf vignetteTitles: package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sizepower/inst/doc/sizepower.R suggestsMe: oneChannelGUI Package: SJava Version: 0.86.0 Depends: R (>= 2.10.0), methods Imports: methods License: GPL (>= 2) MD5sum: c58b2b820dc42a68cdb8fdd805148780 NeedsCompilation: yes Title: The Omegahat interface for R and Java. Description: An interface from R to Java to create and call Java objects and methods. biocViews: Infrastructure Author: Duncan Temple Lang, John Chambers Maintainer: Martin Morgan source.ver: src/contrib/SJava_0.86.0.tar.gz hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: RWebServices importsMe: RWebServices Package: SLGI Version: 1.20.0 Depends: R (>= 2.10), ScISI, lattice Imports: AnnotationDbi, Biobase, GO.db, ScISI, graphics, lattice, methods, stats, BiocGenerics Suggests: GO.db, org.Sc.sgd.db License: Artistic-2.0 MD5sum: 294a10a63b3737f4f237ef4831556c6d NeedsCompilation: no Title: Synthetic Lethal Genetic Interaction Description: A variety of data files and functions for the analysis of genetic interactions biocViews: GraphsAndNetworks, Proteomics, Genetics, NetworkAnalysis Author: Nolwenn LeMeur, Zhen Jiang, Ting-Yuan Liu, Jess Mar and Robert Gentleman Maintainer: Nolwenn Le Meur source.ver: src/contrib/SLGI_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SLGI_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SLGI_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SLGI_1.20.0.tgz vignettes: vignettes/SLGI/inst/doc/SLGI.pdf vignetteTitles: SLGI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SLGI/inst/doc/SLGI.R dependsOnMe: PCpheno Package: SLqPCR Version: 1.26.0 Depends: R(>= 2.4.0) Imports: stats Suggests: RColorBrewer License: GPL (>= 2) MD5sum: cea1ecb13b6ef9992fcae86968424c2a NeedsCompilation: no Title: Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH Description: Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH biocViews: Bioinformatics, MicrotitrePlateAssay, qPCR Author: Matthias Kohl Maintainer: Matthias Kohl source.ver: src/contrib/SLqPCR_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SLqPCR_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SLqPCR_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SLqPCR_1.26.0.tgz vignettes: vignettes/SLqPCR/inst/doc/SLqPCR.pdf vignetteTitles: SLqPCR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SLqPCR/inst/doc/SLqPCR.R suggestsMe: EasyqpcR Package: SMAP Version: 1.24.0 Depends: R (>= 2.10), methods License: GPL-2 Archs: i386, x64 MD5sum: 2c3ff9eebf82f4b840c357dc918fdcd7 NeedsCompilation: yes Title: A Segmental Maximum A Posteriori Approach to Array-CGH Copy Number Profiling Description: Functions and classes for DNA copy number profiling of array-CGH data biocViews: Microarray, TwoChannel, CopyNumberVariants Author: Robin Andersson Maintainer: Robin Andersson source.ver: src/contrib/SMAP_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SMAP_1.24.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SMAP_1.24.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SMAP_1.24.0.tgz vignettes: vignettes/SMAP/inst/doc/SMAP.pdf vignetteTitles: SMAP hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SMAP/inst/doc/SMAP.R Package: SNAGEE Version: 1.0.0 Depends: R (>= 2.6.0), SNAGEEdata Suggests: ALL, hgu95av2.db Enhances: multicore License: Artistic-2.0 MD5sum: 2996c801268b84df6b2b5027b428c80f NeedsCompilation: no Title: Signal-to-Noise applied to Gene Expression Experiments Description: Signal-to-Noise applied to Gene Expression Experiments. Signal-to-noise ratios can be used as a proxy for quality of gene expression studies and samples. The SNRs can be calculated on any gene expression data set as long as gene IDs are available, no access to the raw data files is necessary. This allows to flag problematic studies and samples in any public data set. biocViews: Microarray, OneChannel, TwoChannel, QualityControl Author: David Venet Maintainer: David Venet URL: http://bioconductor.org/ source.ver: src/contrib/SNAGEE_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SNAGEE_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SNAGEE_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SNAGEE_1.0.0.tgz vignettes: vignettes/SNAGEE/inst/doc/SNAGEE.pdf vignetteTitles: SNAGEE Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SNAGEE/inst/doc/SNAGEE.R Package: snapCGH Version: 1.30.0 Depends: limma, DNAcopy, methods Imports: aCGH, cluster, DNAcopy, GLAD, graphics, grDevices, limma, methods, stats, tilingArray, utils License: GPL Archs: i386, x64 MD5sum: 415a4e344c629bf80aa20f66d2c701b1 NeedsCompilation: yes Title: Segmentation, normalisation and processing of aCGH data. Description: Methods for segmenting, normalising and processing aCGH data; including plotting functions for visualising raw and segmented data for individual and multiple arrays. biocViews: Microarray, CopyNumberVariants, TwoChannel, Preprocessing Author: Mike L. Smith, John C. Marioni, Steven McKinney, Thomas Hardcastle, Natalie P. Thorne Maintainer: John Marioni source.ver: src/contrib/snapCGH_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/snapCGH_1.30.0.zip win64.binary.ver: bin/windows64/contrib/2.16/snapCGH_1.30.0.zip mac.binary.ver: bin/macosx/contrib/2.16/snapCGH_1.30.0.tgz vignettes: vignettes/snapCGH/inst/doc/snapCGHguide.pdf vignetteTitles: Segmentation Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/snapCGH/inst/doc/snapCGHguide.R dependsOnMe: ADaCGH2 suggestsMe: beadarraySNP Package: snm Version: 1.8.0 Depends: R(>= 2.12.0), lme4, splines, corpcor License: LGPL MD5sum: 8fb07983ea945eef759544b4f050a8d2 NeedsCompilation: no Title: Supervised Normalization of Microarrays Description: SNM is a modeling strategy especially designed for normalizing high-throughput genomic data. The underlying premise of our approach is that your data is a function of what we refer to as study-specific variables. These variables are either biological variables that represent the target of the statistical analysis, or adjustment variables that represent factors arising from the experimental or biological setting the data is drawn from. The SNM approach aims to simultaneously model all study-specific variables in order to more accurately characterize the biological or clinical variables of interest. biocViews: Microarray, OneChannel, TwoChannel, MultiChannel, DifferentialExpression, ExonArray, GeneExpression, Transcription, MultipleComparisons, Preprocessing, QualityControl Author: Brig Mecham and John D. Storey Maintainer: Brig Mecham source.ver: src/contrib/snm_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/snm_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/snm_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/snm_1.8.0.tgz vignettes: vignettes/snm/inst/doc/snm.pdf vignetteTitles: snm Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/snm/inst/doc/snm.R Package: SNPchip Version: 2.6.0 Depends: R (>= 2.14.0) Imports: graphics, lattice, grid, foreach, utils, methods, oligoClasses (>= 1.21.12), Biobase, GenomicRanges Suggests: crlmm (>= 1.17.14), IRanges, RUnit Enhances: doSNOW, VanillaICE (>= 1.21.24), RColorBrewer License: LGPL (>= 2) MD5sum: 5897b600b6c936e6a84002c423f6d52d NeedsCompilation: no Title: Visualizations for copy number alterations Description: This package defines methods for visualizing high-throughput genomic data biocViews: CopyNumberVariants, SNP, GeneticVariability, Visualization Author: Robert Scharpf and Ingo Ruczinski Maintainer: Robert Scharpf URL: http://www.biostat.jhsph.edu/~iruczins/software/snpchip.html source.ver: src/contrib/SNPchip_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SNPchip_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SNPchip_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SNPchip_2.6.0.tgz vignettes: vignettes/SNPchip/inst/doc/PlottingIdiograms.pdf vignetteTitles: Plotting Idiograms hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SNPchip/inst/doc/PlottingIdiograms.R dependsOnMe: mBPCR importsMe: crlmm, phenoTest suggestsMe: Category, MinimumDistance, oligoClasses, VanillaICE Package: snpStats Version: 1.10.0 Depends: R(>= 2.10.0), survival, methods, Matrix Imports: graphics, grDevices, methods, stats, survival, utils, Matrix, BiocGenerics Suggests: hexbin License: GPL-3 Archs: i386, x64 MD5sum: 852e2fbb94509a83f0e88579b516fc0d NeedsCompilation: yes Title: SnpMatrix and XSnpMatrix classes and methods Description: Classes and statistical methods for large SNP association studies, extending the snpMatrix package (now removed) biocViews: Microarray, SNP, GeneticVariability Author: David Clayton Maintainer: David Clayton source.ver: src/contrib/snpStats_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/snpStats_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/snpStats_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/snpStats_1.10.0.tgz vignettes: vignettes/snpStats/inst/doc/data-input-vignette.pdf, vignettes/snpStats/inst/doc/differences.pdf, vignettes/snpStats/inst/doc/imputation-vignette.pdf, vignettes/snpStats/inst/doc/ld-vignette.pdf, vignettes/snpStats/inst/doc/pca-vignette.pdf, vignettes/snpStats/inst/doc/snpStats-vignette.pdf, vignettes/snpStats/inst/doc/tdt-vignette.pdf vignetteTitles: Data input, snpMatrix-differences, Imputation and meta-analysis, LD statistics, Principal components analysis, snpStats introduction, TDT tests hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/snpStats/inst/doc/data-input-vignette.R, vignettes/snpStats/inst/doc/differences.R, vignettes/snpStats/inst/doc/imputation-vignette.R, vignettes/snpStats/inst/doc/ld-vignette.R, vignettes/snpStats/inst/doc/pca-vignette.R, vignettes/snpStats/inst/doc/snpStats-vignette.R, vignettes/snpStats/inst/doc/tdt-vignette.R dependsOnMe: GGBase, gwascat importsMe: FunciSNP, GGtools suggestsMe: crlmm, GWASTools, VariantAnnotation Package: SomatiCA Version: 1.0.0 Depends: R (>= 2.14.0), lars, DNAcopy, foreach, methods, rebmix, GenomicRanges, IRanges, doParallel Imports: foreach, lars, sn, DNAcopy, methods, rebmix, GenomicRanges, IRanges Enhances: sn, SomatiCAData License: GPL (>=2) MD5sum: bc264abe23ab22ac9472949d613863cc NeedsCompilation: no Title: SomatiCA: identifying, characterizing, and quantifying somatic copy number aberrations from cancer genome sequencing Description: SomatiCA is a software suite that is capable of identifying, characterizing, and quantifying somatic CNAs from cancer genome sequencing. First, it uses read depths and lesser allele frequencies (LAF) from mapped short sequence reads to segment the genome and identify candidate CNAs. Second, SomatiCA estimates the admixture rate from the relative copy-number profile of tumor-normal pair by a Bayesian finite mixture model. Third, SomatiCA quantifies absolute somatic copy-number and subclonality for each genomic segment to guide its characterization. Results from SomatiCA can be further integrated with single nucleotide variations (SNVs) to get a better understanding of the tumor evolution. biocViews: Bioinformatics, Sequencing, CopyNumberVariants Author: Mengjie Chen , Hongyu Zhao Maintainer: Mengjie Chen source.ver: src/contrib/SomatiCA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SomatiCA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SomatiCA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SomatiCA_1.0.0.tgz vignettes: vignettes/SomatiCA/inst/doc/SomatiCA.pdf, vignettes/SomatiCA/inst/doc/SomatiCAUsersGuide.pdf vignetteTitles: SomatiCA Vignette, SomatiCAUsersGuide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SomatiCA/inst/doc/SomatiCA.R Package: spade Version: 1.8.0 Depends: R (>= 2.11), igraph0 Imports: Biobase, flowCore Suggests: flowViz License: GPL-2 Archs: i386, x64 MD5sum: a1b7a22744dc693e732e096fed0bc9b1 NeedsCompilation: yes Title: SPADE -- An analysis and visualization tool for Flow Cytometry Description: SPADE, or Spanning tree Progression of Density normalized Events, is an analysis and visualization tool for high dimensional flow cytometry data that organizes cells into hierarchies of related phenotypes. biocViews: FlowCytometry, GraphsAndNetworks, GUI, Visualization, Clustering Author: M. Linderman, P. Qiu, E. Simonds, Z. Bjornson Maintainer: Michael Linderman URL: http://cytospade.org source.ver: src/contrib/spade_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/spade_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/spade_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/spade_1.8.0.tgz vignettes: vignettes/spade/inst/doc/SPADE.pdf vignetteTitles: spade package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/spade/inst/doc/SPADE.R Package: SpeCond Version: 1.14.0 Depends: R (>= 2.10.0), mclust (>= 3.3.1), Biobase (>= 1.15.13), fields, hwriter (>= 1.1), RColorBrewer, methods License: LGPL (>=2) MD5sum: 42c95f023fc22c82117c30b8f00adc63 NeedsCompilation: no Title: Condition specific detection from expression data Description: This package performs a gene expression data analysis to detect condition-specific genes. Such genes are significantly up- or down-regulated in a small number of conditions. It does so by fitting a mixture of normal distributions to the expression values. Conditions can be environmental conditions, different tissues, organs or any other sources that you wish to compare in terms of gene expression. biocViews: Microarray, DifferentialExpression, Bioinformatics, MultipleComparisons, Clustering, ReportWriting Author: Florence Cavalli Maintainer: Florence Cavalli source.ver: src/contrib/SpeCond_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SpeCond_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SpeCond_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SpeCond_1.14.0.tgz vignettes: vignettes/SpeCond/inst/doc/SpeCond.pdf vignetteTitles: SpeCond hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SpeCond/inst/doc/SpeCond.R Package: SPEM Version: 1.0.0 Depends: R (>= 2.15.1), Rsolnp, Biobase, methods License: GPL-2 MD5sum: ee41df7c640acc06e950caa64de4eb99 NeedsCompilation: no Title: S-system parameter estimation method Description: This package can optimize the parameter in S-system models given time series data biocViews: Bioinformatics, NetworkAnalysis, NetworkInference, Software Author: Xinyi YANG Developer, Jennifer E. DENT Developer and Christine NARDINI Supervisor Maintainer: Xinyi YANG source.ver: src/contrib/SPEM_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SPEM_1.0.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SPEM_1.0.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SPEM_1.0.0.tgz vignettes: vignettes/SPEM/inst/doc/Flowchartmain.pdf, vignettes/SPEM/inst/doc/sospathway.pdf, vignettes/SPEM/inst/doc/SPEM-package.pdf, vignettes/SPEM/inst/doc/S_system.pdf vignetteTitles: Flowchartmain.pdf, sospathway.pdf, Vignette for SPEM, S_system.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SPEM/inst/doc/SPEM-package.R Package: SPIA Version: 2.12.0 Depends: R (>= 2.14.0), graphics, KEGGgraph Imports: graphics Suggests: graph, Rgraphviz, hgu133plus2.db License: GPL (>= 2) MD5sum: b5c68b43c61fad4474f952fa62a22a0e NeedsCompilation: no Title: Signaling Pathway Impact Analysis (SPIA) using combined evidence of pathway over-representation and unusual signaling perturbations Description: This package implements the Signaling Pathway Impact Analysis (SPIA) which uses the information form a list of differentially expressed genes and their log fold changes together with signaling pathways topology, in order to identify the pathways most relevant to the condition under the study. biocViews: Microarray, GraphsAndNetworks Author: Adi Laurentiu Tarca , Purvesh Kathri and Sorin Draghici Maintainer: Adi Laurentiu Tarca URL: http://bioinformatics.oxfordjournals.org/cgi/reprint/btn577v1 source.ver: src/contrib/SPIA_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SPIA_2.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SPIA_2.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SPIA_2.12.0.tgz vignettes: vignettes/SPIA/inst/doc/SPIA.pdf vignetteTitles: SPIA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SPIA/inst/doc/SPIA.R suggestsMe: graphite, KEGGgraph Package: spikeLI Version: 2.20.0 Imports: graphics, grDevices, stats, utils License: GPL-2 MD5sum: 161a08fd80842f5dd0b4c972904c0041 NeedsCompilation: no Title: Affymetrix Spike-in Langmuir Isotherm Data Analysis Tool Description: SpikeLI is a package that performs the analysis of the Affymetrix spike-in data using the Langmuir Isotherm. The aim of this package is to show the advantages of a physical-chemistry based analysis of the Affymetrix microarray data compared to the traditional methods. The spike-in (or Latin square) data for the HGU95 and HGU133 chipsets have been downloaded from the Affymetrix web site. The model used in the spikeLI package is described in details in E. Carlon and T. Heim, Physica A 362, 433 (2006). biocViews: Microarray, QualityControl Author: Delphine Baillon, Paul Leclercq , Sarah Ternisien, Thomas Heim, Enrico Carlon Maintainer: Enrico Carlon source.ver: src/contrib/spikeLI_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/spikeLI_2.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/spikeLI_2.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/spikeLI_2.20.0.tgz vignettes: vignettes/spikeLI/inst/doc/collapse_A14.pdf, vignettes/spikeLI/inst/doc/Ivsc.pdf, vignettes/spikeLI/inst/doc/IvsDG_TagE.pdf, vignettes/spikeLI/inst/doc/langmuir2.pdf, vignettes/spikeLI/inst/doc/spikeLI.pdf vignetteTitles: collapse_A14.pdf, Ivsc.pdf, IvsDG_TagE.pdf, langmuir2.pdf, spikeLI hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spikeLI/inst/doc/spikeLI.R Package: spkTools Version: 1.16.0 Depends: R (>= 2.7.0), Biobase (>= 2.5.5) Imports: Biobase (>= 2.5.5), graphics, grDevices, gtools, methods, RColorBrewer, stats, utils Suggests: xtable License: GPL (>= 2) MD5sum: c6ba119c5f9393eeab1a2e1d8f912787 NeedsCompilation: no Title: Methods for Spike-in Arrays Description: The package contains functions that can be used to compare expression measures on different array platforms. biocViews: Software, AssayTechnologies, Microarray Author: Matthew N McCall , Rafael A Irizarry Maintainer: Matthew N McCall URL: http://bioconductor.org source.ver: src/contrib/spkTools_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/spkTools_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/spkTools_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/spkTools_1.16.0.tgz vignettes: vignettes/spkTools/inst/doc/spkDoc.pdf vignetteTitles: spkTools: Spike-in Data Analysis and Visualization hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spkTools/inst/doc/spkDoc.R Package: splicegear Version: 1.32.0 Depends: R (>= 2.6.0), methods, Biobase(>= 2.5.5) Imports: annotate, Biobase, graphics, grDevices, grid, methods, utils, XML License: LGPL MD5sum: d0cc295b63bfd43360e1cd8a788f55e1 NeedsCompilation: no Title: splicegear Description: A set of tools to work with alternative splicing biocViews: Infrastructure, Transcription Author: Laurent Gautier Maintainer: Laurent Gautier source.ver: src/contrib/splicegear_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/splicegear_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/splicegear_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/splicegear_1.32.0.tgz vignettes: vignettes/splicegear/inst/doc/splicegear.pdf vignetteTitles: splicegear Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/splicegear/inst/doc/splicegear.R Package: SplicingGraphs Version: 1.0.4 Depends: BiocGenerics, IRanges (>= 1.17.43), GenomicRanges (>= 1.11.45), GenomicFeatures, Rgraphviz (>= 2.3.7) Imports: methods, utils, igraph, BiocGenerics, IRanges, GenomicRanges, GenomicFeatures, graph, Rgraphviz Suggests: igraph, Gviz, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene, RNAseqData.HNRNPC.bam.chr14, RUnit License: Artistic-2.0 MD5sum: 0407eb8d437a81c273c335b10596d334 NeedsCompilation: no Title: Create, manipulate, visualize splicing graphs, and assign RNA-seq reads to them Description: This package allows the user to create, manipulate, and visualize splicing graphs and their bubbles based on a gene model for a given organism. Additionally it allows the user to assign RNA-seq reads to the edges of a set of splicing graphs, and to summarize them in different ways. biocViews: Genetics, Annotation, DataRepresentation, Visualization, Sequencing, RNAseq, GeneExpression Author: D. Bindreither, M. Carlson, M. Morgan, H. Pages Maintainer: H. Pages source.ver: src/contrib/SplicingGraphs_1.0.4.tar.gz win.binary.ver: bin/windows/contrib/2.16/SplicingGraphs_1.0.4.zip win64.binary.ver: bin/windows64/contrib/2.16/SplicingGraphs_1.0.4.zip mac.binary.ver: bin/macosx/contrib/2.16/SplicingGraphs_1.0.4.tgz vignettes: vignettes/SplicingGraphs/inst/doc/SplicingGraphs.pdf vignetteTitles: Splicing graphs and RNA-seq data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SplicingGraphs/inst/doc/SplicingGraphs.R Package: splots Version: 1.26.0 Imports: grid, RColorBrewer License: LGPL MD5sum: 0d23dd5a45df496bbbc341186e445c84 NeedsCompilation: no Title: Visualization of high-throughput assays in microtitre plate or slide format Description: The splots package provides the plotScreen function for visualising data in microtitre plate or slide format. biocViews: Visualization, HighThroughputSequencing, MicrotitrePlateAssay Author: Wolfgang Huber, Oleg Sklyar Maintainer: Wolfgang Huber source.ver: src/contrib/splots_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/splots_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/splots_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/splots_1.26.0.tgz vignettes: vignettes/splots/inst/doc/splotsHOWTO.pdf vignetteTitles: Visualization of data from assays in microtitre plate or slide format hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/splots/inst/doc/splotsHOWTO.R dependsOnMe: cellHTS2 importsMe: RNAinteract, RNAither Package: spotSegmentation Version: 1.34.0 Depends: R (>= 2.10), mclust License: GPL (>= 2) MD5sum: bb399e2a497da2a599155749d8534ab3 NeedsCompilation: no Title: Microarray Spot Segmentation and Gridding for Blocks of Microarray Spots Description: Spot segmentation via model-based clustering and gridding for blocks within microarray slides, as described in Li et al, Robust Model-Based Segmentation of Microarray Images, Technical Report no. 473, Department of Statistics, University of Washington. biocViews: Microarray, TwoChannel, QualityControl, Preprocessing Author: Qunhua Li, Chris Fraley, Adrian Raftery Department of Statistics, University of Washington Maintainer: Chris Fraley URL: http://www.stat.washington.edu/fraley source.ver: src/contrib/spotSegmentation_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/spotSegmentation_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/spotSegmentation_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/spotSegmentation_1.34.0.tgz vignettes: vignettes/spotSegmentation/inst/doc/spotsegdoc.pdf vignetteTitles: spotsegdoc.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: SQUADD Version: 1.10.0 Depends: R (>= 2.11.0) Imports: graphics, grDevices, methods, RColorBrewer, stats, utils License: GPL (>=2) MD5sum: c6bb895cbff10083615869fd5a92aea9 NeedsCompilation: no Title: Add-on of the SQUAD Software Description: This package SQUADD is a SQUAD add-on. It permits to generate SQUAD simulation matrix, prediction Heat-Map and Correlation Circle from PCA analysis. biocViews: GraphsAndNetworks, NetworkAnalysis, Visualization Author: Martial Sankar, supervised by Christian Hardtke and Ioannis Xenarios Maintainer: Martial Sankar URL: http://www.unil.ch/dbmv/page21142_en.html source.ver: src/contrib/SQUADD_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SQUADD_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SQUADD_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SQUADD_1.10.0.tgz vignettes: vignettes/SQUADD/inst/doc/SQUADD_ERK.pdf, vignettes/SQUADD/inst/doc/SQUADD.pdf vignetteTitles: SQUADD package, SQUADD package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SQUADD/inst/doc/SQUADD_ERK.R, vignettes/SQUADD/inst/doc/SQUADD.R Package: SRAdb Version: 1.14.0 Depends: RSQLite (>= 0.8-4) , graph, RCurl Imports: GEOquery Suggests: Rgraphviz License: Artistic-2.0 MD5sum: 710f11168accd61aa24ada8aba4f9217 NeedsCompilation: no Title: A compilation of metadata from NCBI SRA and tools Description: The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, and others. However, finding data of interest can be challenging using current tools. SRAdb is an attempt to make access to the metadata associated with submission, study, sample, experiment and run much more feasible. This is accomplished by parsing all the NCBI SRA metadata into a SQLite database that can be stored and queried locally. Fulltext search in the package make querying metadata very flexible and powerful. fastq and sra files can be downloaded for doing alignment locally. Beside ftp protocol, the SRAdb has funcitons supporting fastp protocol (ascp from Aspera Connect) for faster downloading large data files over long distance. The SQLite database is updated regularly as new data is added to SRA and can be downloaded at will for the most up-to-date metadata. biocViews: Infrastructure, HighThroughputSequencing, DataImport Author: Jack Zhu and Sean Davis Maintainer: Jack Zhu URL: http://gbnci.abcc.ncifcrf.gov/sra/ source.ver: src/contrib/SRAdb_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/SRAdb_1.14.0.zip win64.binary.ver: bin/windows64/contrib/2.16/SRAdb_1.14.0.zip mac.binary.ver: bin/macosx/contrib/2.16/SRAdb_1.14.0.tgz vignettes: vignettes/SRAdb/inst/doc/SRAdb.pdf vignetteTitles: Using SRAdb to Query the Sequence Read Archive hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SRAdb/inst/doc/SRAdb.R Package: sscore Version: 1.32.0 Depends: R (>= 1.8.0), affy, affyio Suggests: affydata License: GPL (>= 2) MD5sum: 843f361d34a36140c6e4403973bfad6e NeedsCompilation: no Title: S-Score Algorithm for Affymetrix Oligonucleotide Microarrays Description: This package contains an implementation of the S-Score algorithm as described by Zhang et al (2002). biocViews: Bioinformatics, DifferentialExpression Author: Richard Kennedy , based on C++ code from Li Zhang and Borland Delphi code from Robnet Kerns . Maintainer: Richard Kennedy URL: http://home.att.net/~richard-kennedy/professional.html source.ver: src/contrib/sscore_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/sscore_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/sscore_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/sscore_1.32.0.tgz vignettes: vignettes/sscore/inst/doc/sscore.pdf vignetteTitles: SScore primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sscore/inst/doc/sscore.R Package: ssize Version: 1.34.0 Depends: gdata, xtable License: LGPL MD5sum: a4e384ee4c3c87f673555a9c5c8ffda3 NeedsCompilation: no Title: Estimate Microarray Sample Size Description: Functions for computing and displaying sample size information for gene expression arrays. biocViews: Bioinformatics, Microarray, DifferentialExpression Author: Gregory R. Warnes, Peng Liu, and Fasheng Li Maintainer: Gregory R. Warnes source.ver: src/contrib/ssize_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ssize_1.34.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ssize_1.34.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ssize_1.34.0.tgz vignettes: vignettes/ssize/inst/doc/ssize.pdf vignetteTitles: package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ssize/inst/doc/ssize.R suggestsMe: oneChannelGUI Package: SSPA Version: 2.0.3 Depends: R (>= 2.12), methods, qvalue, lattice, limma Imports: graphics, stats Suggests: genefilter, edgeR, DESeq License: GPL (>= 2) Archs: i386, x64 MD5sum: 023edd4b3ca28858f97df804f93aad63 NeedsCompilation: yes Title: General Sample Size and Power Analysis for Microarray and Next-Generation Sequencing Data Description: General Sample size and power analysis for microarray and next-generation sequencing data. biocViews: Microarray, Statistics Author: Maarten van Iterson Maintainer: Maarten van Iterson URL: http://www.humgen.nl/MicroarrayAnalysisGroup.html source.ver: src/contrib/SSPA_2.0.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/SSPA_2.0.3.zip win64.binary.ver: bin/windows64/contrib/2.16/SSPA_2.0.3.zip mac.binary.ver: bin/macosx/contrib/2.16/SSPA_2.0.3.tgz vignettes: vignettes/SSPA/inst/doc/SSPA.pdf vignetteTitles: SSPA Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SSPA/inst/doc/SSPA.R Package: staRank Version: 1.2.0 Depends: methods, cellHTS2, R (>= 2.10) License: GPL MD5sum: 950a257b58cbf2677ec8fdd4802e8c6f NeedsCompilation: no Title: Stability Ranking Description: Detecting all relevant variables from a data set is challenging, especially when only few samples are available and data is noisy. Stability ranking provides improved variable rankings of increased robustness using resampling or subsampling. biocViews: Bioinformatics, MultipleComparisons, CellBiology, CellBasedAssays, MicrotitrePlateAssay Author: Juliane Siebourg, Niko Beerenwinkel Maintainer: Juliane Siebourg source.ver: src/contrib/staRank_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/staRank_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/staRank_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/staRank_1.2.0.tgz vignettes: vignettes/staRank/inst/doc/staRank.pdf vignetteTitles: Using staRank hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/staRank/inst/doc/staRank.R Package: Starr Version: 1.16.0 Depends: Ringo, affy, affxparser Imports: pspline, MASS, zlibbioc License: Artistic-2.0 Archs: i386, x64 MD5sum: b06f73ca43519f0f8a5b636c3dcd2630 NeedsCompilation: yes Title: Simple tiling array analysis of Affymetrix ChIP-chip data Description: Starr facilitates the analysis of ChIP-chip data, in particular that of Affymetrix tiling arrays. The package provides functions for data import, quality assessment, data visualization and exploration. Furthermore, it includes high-level analysis features like association of ChIP signals with annotated features, correlation analysis of ChIP signals and other genomic data (e.g. gene expression), peak-finding with the CMARRT algorithm and comparative display of multiple clusters of ChIP-profiles. It uses the basic Bioconductor classes ExpressionSet and probeAnno for maximum compatibility with other software on Bioconductor. All functions from Starr can be used to investigate preprocessed data from the Ringo package, and vice versa. An important novel tool is the the automated generation of correct, up-to-date microarray probe annotation (bpmap) files, which relies on an efficient mapping of short sequences (e.g. the probe sequences on a microarray) to an arbitrary genome. biocViews: Microarray,OneChannel,DataImport,QualityControl,Preprocessing,ChIPchip Author: Benedikt Zacher, Johannes Soeding, Pei Fen Kuan, Matthias Siebert, Achim Tresch Maintainer: Benedikt Zacher source.ver: src/contrib/Starr_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Starr_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Starr_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Starr_1.16.0.tgz vignettes: vignettes/Starr/inst/doc/Starr.pdf vignetteTitles: Simple tiling array analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Starr/inst/doc/Starr.R Package: stepNorm Version: 1.32.0 Depends: R (>= 1.8.0), marray, methods Imports: marray, MASS, methods, stats License: LGPL MD5sum: 284878053f77d4eaeb3c0491727045ce NeedsCompilation: no Title: Stepwise normalization functions for cDNA microarrays Description: Stepwise normalization functions for cDNA microarray data. biocViews: Microarray, TwoChannel, Preprocessing Author: Yuanyuan Xiao , Yee Hwa (Jean) Yang Maintainer: Yuanyuan Xiao URL: http://www.biostat.ucsf.edu/jean/ source.ver: src/contrib/stepNorm_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/stepNorm_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/stepNorm_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/stepNorm_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: stepwiseCM Version: 1.6.0 Depends: R (>= 2.14), randomForest, MAclinical, tspair, pamr, snowfall, glmpath, penalized, e1071 License: GPL (http://www.gnu.org/copyleft/gpl.html) MD5sum: 20edd5f9d76f9eef69760ecd5a0e7a15 NeedsCompilation: no Title: Stepwise Classification of Cancer Samples using Clinical and Molecular Data Description: Stepwise classification of cancer samples using both clinical and molecular data Author: Askar Obulkasim Maintainer: Askar Obulkasim source.ver: src/contrib/stepwiseCM_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/stepwiseCM_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/stepwiseCM_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/stepwiseCM_1.6.0.tgz vignettes: vignettes/stepwiseCM/inst/doc/stepwiseCM.pdf vignetteTitles: stepwiseCM hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/stepwiseCM/inst/doc/stepwiseCM.R Package: Streamer Version: 1.6.0 Imports: methods, graph, RBGL, parallel, BiocGenerics Suggests: RUnit, Rsamtools (>= 1.5.53), Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: 9dbf7aaf53792be564939ef4492e72a4 NeedsCompilation: yes Title: Enabling stream processing of large files Description: Large data files can be difficult to work with in R, where data generally resides in memory. This package encourages a style of programming where data is 'streamed' from disk into R via a `producer' and through a series of `consumers' that, typically reduce the original data to a manageable size. The package provides useful Producer and Consumer stream components for operations such as data input, sampling, indexing, and transformation; see package?Streamer for details. biocViews: Infrastructure, DataImport Author: Martin Morgan, Nishant Gopalakrishnan Maintainer: Martin Morgan source.ver: src/contrib/Streamer_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Streamer_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Streamer_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Streamer_1.6.0.tgz vignettes: vignettes/Streamer/inst/doc/Streamer.pdf vignetteTitles: Streamer: A simple example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Streamer/inst/doc/Streamer.R Package: survcomp Version: 1.10.0 Depends: R (>= 2.10), survival, prodlim Imports: ipred, SuppDists, KernSmooth, survivalROC, bootstrap, grid, rmeta Suggests: Hmisc, CPE, clinfun, survJamda, Biobase, xtable License: Artistic-2.0 Archs: i386, x64 MD5sum: 96b1b0133bd438c68d6a02d6d55bf561 NeedsCompilation: yes Title: Performance Assessment and Comparison for Survival Analysis Description: R package providing functions to assess and to compare the performance of risk prediction (survival) models. biocViews: GeneExpression, DifferentialExpression, Visualization Author: Benjamin Haibe-Kains, Markus Schroeder, Catharina Olsen, Christos Sotiriou, Gianluca Bontempi, John Quackenbush Maintainer: Benjamin Haibe-Kains , Markus Schroeder , Catharina Olsen URL: http://compbio.dfci.harvard.edu source.ver: src/contrib/survcomp_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/survcomp_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/survcomp_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/survcomp_1.10.0.tgz vignettes: vignettes/survcomp/inst/doc/survcomp.pdf vignetteTitles: SurvComp: a package for performance assessment and comparison for survival analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/survcomp/inst/doc/survcomp.R dependsOnMe: genefu Package: sva Version: 3.6.0 Depends: R (>= 2.8), corpcor, mgcv Imports: graphics, stats Suggests: limma,pamr,bladderbatch License: Artistic-2.0 Archs: i386, x64 MD5sum: 505ff744cc6fd66dc8f85f420dc0898f NeedsCompilation: yes Title: Surrogate Variable Analysis Description: The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in two ways: (1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS) and (2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics). Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics). Surrogate variable analysis and ComBat were developed in the context of microarray experiments, but may be used as a general tool for high throughput data sets where dependence may be involved. biocViews: Microarray,Statistics,Preprocessing,MultipleComparisons Author: Jeffrey T. Leek , W. Evan Johnson , Hilary S. Parker , Andrew E. Jaffe , John D. Storey , Maintainer: Jeffrey T. Leek source.ver: src/contrib/sva_3.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/sva_3.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/sva_3.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/sva_3.6.0.tgz vignettes: vignettes/sva/inst/doc/sva.pdf vignetteTitles: bladderbatchTutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sva/inst/doc/sva.R importsMe: trigger Package: synapter Version: 1.2.0 Depends: R (>= 2.15), methods, MSnbase Imports: hwriter, tcltk, tcltk2, RColorBrewer, lattice, qvalue, multtest, utils, Biobase, knitr Suggests: synapterdata, xtable License: GPL-2 MD5sum: 3e45a9e19052efc2ad8c5188c3ac01ed NeedsCompilation: no Title: Label-free data analysis pipeline for optimal identification and quantitation Description: The synapter package provides functionality to reanalyse label-free proteomics data acquired on a Synapt G2 mass spectrometer. One or several runs, possibly processed with additional ion mobility separation to increase identification accuracy can be combined to other quantitation files to maximise identification and quantitation accuracy. biocViews: Bioinformatics, MassSpectrometry, Proteomics, GUI Author: Laurent Gatto, Nick J. Bond and Pavel V. Shliaha Maintainer: Laurent Gatto URL: http://lgatto.github.com/synapter/ VignetteBuilder: knitr source.ver: src/contrib/synapter_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/synapter_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/synapter_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/synapter_1.2.0.tgz vignettes: vignettes/synapter/inst/doc/synapter.pdf vignetteTitles: Combining HDMSe/MSe data using 'synapter' to optimise identification and quantitation hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/synapter/inst/doc/synapter.R Package: TargetSearch Version: 1.16.0 Depends: R (>= 2.7.0), mzR, methods Imports: graphics, grDevices, methods, stats, tcltk, utils Suggests: TargetSearchData License: GPL (>= 2) Archs: i386, x64 MD5sum: 30e788a8279982ff93b04a9be5065a0b NeedsCompilation: yes Title: A package for the analysis of GC-MS metabolite profiling data. Description: This packages provides a targeted pre-processing method for GC-MS data. biocViews: MassSpectrometry,Preprocessing Author: Alvaro Cuadros-Inostroza , Jan Lisec , Henning Redestig , Matt Hannah Maintainer: Alvaro Cuadros-Inostroza source.ver: src/contrib/TargetSearch_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/TargetSearch_1.16.0.zip win64.binary.ver: bin/windows64/contrib/2.16/TargetSearch_1.16.0.zip mac.binary.ver: bin/macosx/contrib/2.16/TargetSearch_1.16.0.tgz vignettes: vignettes/TargetSearch/inst/doc/RICorrection.pdf, vignettes/TargetSearch/inst/doc/TargetSearch.pdf vignetteTitles: RI correction, The TargetSearch Package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TargetSearch/inst/doc/RICorrection.R, vignettes/TargetSearch/inst/doc/TargetSearch.R Package: TDARACNE Version: 1.10.0 Depends: GenKern, Rgraphviz, Biobase License: GPL-2 MD5sum: c2916a4e62e9e983ddb723845093031f NeedsCompilation: no Title: Network reverse engineering from time course data. Description: To infer gene networks from time-series measurements is a current challenge into bioinformatics research area. In order to detect dependencies between genes at different time delays, we propose an approach to infer gene regulatory networks from time-series measurements starting from a well known algorithm based on information theory. The proposed algorithm is expected to be useful in reconstruction of small biological directed networks from time course data. biocViews: Microarray, TimeCourse Author: Zoppoli P.,Morganella S., Ceccarelli M. Maintainer: Zoppoli Pietro source.ver: src/contrib/TDARACNE_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/TDARACNE_1.10.0.zip win64.binary.ver: bin/windows64/contrib/2.16/TDARACNE_1.10.0.zip mac.binary.ver: bin/macosx/contrib/2.16/TDARACNE_1.10.0.tgz vignettes: vignettes/TDARACNE/inst/doc/TDARACNE.pdf vignetteTitles: TDARACNE hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TDARACNE/inst/doc/TDARACNE.R Package: TEQC Version: 2.9.2 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.5), Rsamtools, hwriter Imports: Biobase (>= 2.15.1) License: GPL (>= 2) MD5sum: e1b3262a0fa522d0e415d77fd0d27ebf NeedsCompilation: no Title: Quality control for target capture experiments Description: Target capture experiments combine hybridization-based (in solution or on microarrays) capture and enrichment of genomic regions of interest (e.g. the exome) with high throughput sequencing of the captured DNA fragments. This package provides functionalities for assessing and visualizing the quality of the target enrichment process, like specificity and sensitivity of the capture, per-target read coverage and so on. biocViews: QualityControl, Microarray, HighThroughputSequencing, Bioinformatics, Genetics Author: M. Hummel, S. Bonnin, E. Lowy, G. Roma Maintainer: Manuela Hummel source.ver: src/contrib/TEQC_2.9.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/TEQC_2.9.2.zip win64.binary.ver: bin/windows64/contrib/2.16/TEQC_2.9.2.zip mac.binary.ver: bin/macosx/contrib/2.16/TEQC_2.9.2.tgz vignettes: vignettes/TEQC/inst/doc/TEQC.pdf vignetteTitles: TEQC hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TEQC/inst/doc/TEQC.R Package: ternarynet Version: 1.4.0 Depends: R (>= 2.10.0), methods Imports: utils, igraph License: GPL (>= 2) Archs: i386, x64 MD5sum: eecda91fcf771aa67d12cf60fdecd874 NeedsCompilation: yes Title: Ternary Network Estimation Description: A computational Bayesian approach to ternary gene regulatory network estimation from gene perturbation experiments. biocViews: Software, CellBiology, GraphsAndNetworks, Bioinformatics Author: Matthew N. McCall , Anthony Almudevar Maintainer: Matthew N. McCall source.ver: src/contrib/ternarynet_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/ternarynet_1.4.0.zip win64.binary.ver: bin/windows64/contrib/2.16/ternarynet_1.4.0.zip mac.binary.ver: bin/macosx/contrib/2.16/ternarynet_1.4.0.tgz vignettes: vignettes/ternarynet/inst/doc/ternarynet.pdf vignetteTitles: ternarynet: A Computational Bayesian Approach to Ternary Network Estimation hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ternarynet/inst/doc/ternarynet.R Package: tigre Version: 1.14.1 Depends: R (>= 2.11.0), BiocGenerics, Biobase Imports: methods, BiocGenerics, Biobase, AnnotationDbi, gplots, graphics, puma, stats, utils, annotate, DBI, RSQLite Suggests: puma, drosgenome1.db, annotate, lumi License: AGPL-3 Archs: i386, x64 MD5sum: a987596d2146f43df2cf3f50102e998e NeedsCompilation: yes Title: Transcription factor Inference through Gaussian process Reconstruction of Expression Description: The tigre package implements our methodology of Gaussian process differential equation models for analysis of gene expression time series from single input motif networks. The package can be used for inferring unobserved transcription factor (TF) protein concentrations from expression measurements of known target genes, or for ranking candidate targets of a TF. biocViews: Microarray, Bioinformatics, TimeCourse, GeneExpression, Transcription Author: Antti Honkela, Pei Gao, Jonatan Ropponen, Miika-Petteri Matikainen, Magnus Rattray, Neil D. Lawrence Maintainer: Antti Honkela URL: http://www.bioinf.manchester.ac.uk/resources/tiger/ source.ver: src/contrib/tigre_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/tigre_1.14.1.zip win64.binary.ver: bin/windows64/contrib/2.16/tigre_1.14.1.zip mac.binary.ver: bin/macosx/contrib/2.16/tigre_1.14.1.tgz vignettes: vignettes/tigre/inst/doc/tigre.pdf, vignettes/tigre/inst/doc/tigre_quick.pdf vignetteTitles: tigre User Guide, tigre Quick Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tigre/inst/doc/tigre_quick.R, vignettes/tigre/inst/doc/tigre.R Package: tilingArray Version: 1.38.0 Depends: R (>= 2.11.0), Biobase, methods, pixmap Imports: strucchange, affy, vsn, genefilter, RColorBrewer, grid, stats4 License: Artistic-2.0 Archs: i386, x64 MD5sum: 2c286338c006aa25f12ecbffbe5d15f5 NeedsCompilation: yes Title: Transcript mapping with high-density oligonucleotide tiling arrays Description: The package provides functionality that can be useful for the analysis of high-density tiling microarray data (such as from Affymetrix genechips) for measuring transcript abundance and architecture. The main functionalities of the package are: 1. the class 'segmentation' for representing partitionings of a linear series of data; 2. the function 'segment' for fitting piecewise constant models using a dynamic programming algorithm that is both fast and exact; 3. the function 'confint' for calculating confidence intervals using the strucchange package; 4. the function 'plotAlongChrom' for generating pretty plots; 5. the function 'normalizeByReference' for probe-sequence dependent response adjustment from a (set of) reference hybridizations. biocViews: Microarray, OneChannel, Preprocessing, Visualization Author: Wolfgang Huber, Zhenyu Xu, Joern Toedling with contributions from Matt Ritchie Maintainer: Zhenyu Xu source.ver: src/contrib/tilingArray_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/tilingArray_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/tilingArray_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/tilingArray_1.38.0.tgz vignettes: vignettes/tilingArray/inst/doc/assessNorm.pdf, vignettes/tilingArray/inst/doc/costMatrix.pdf, vignettes/tilingArray/inst/doc/findsegments.pdf, vignettes/tilingArray/inst/doc/plotAlongChrom.pdf, vignettes/tilingArray/inst/doc/segmentation.pdf vignetteTitles: Normalisation with the normalizeByReference function in the tilingArray package, Supplement. Calculation of the cost matrix, Introduction to using the segment function to fit a piecewise constant curve, Introduction to the plotAlongChrom function, Segmentation demo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tilingArray/inst/doc/assessNorm.R, vignettes/tilingArray/inst/doc/costMatrix.R, vignettes/tilingArray/inst/doc/findsegments.R, vignettes/tilingArray/inst/doc/plotAlongChrom.R, vignettes/tilingArray/inst/doc/segmentation.R dependsOnMe: ADaCGH2 importsMe: snapCGH Package: timecourse Version: 1.32.0 Depends: R (>= 2.1.1), MASS, methods Imports: Biobase, graphics, limma (>= 1.8.6), MASS, marray, methods, stats License: LGPL MD5sum: 08f0716ada5973b200a9b61aef29f701 NeedsCompilation: no Title: Statistical Analysis for Developmental Microarray Time Course Data Description: Functions for data analysis and graphical displays for developmental microarray time course data. biocViews: Microarray, TimeCourse, DifferentialExpression Author: Yu Chuan Tai Maintainer: Yu Chuan Tai URL: http://www.bioconductor.org source.ver: src/contrib/timecourse_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/timecourse_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/timecourse_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/timecourse_1.32.0.tgz vignettes: vignettes/timecourse/inst/doc/timecourse.pdf vignetteTitles: timecourse manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/timecourse/inst/doc/timecourse.R Package: tkWidgets Version: 1.38.0 Depends: R (>= 2.0.0), methods, widgetTools (>= 1.1.7), DynDoc (>= 1.3.0), tools Suggests: Biobase, hgu95av2 License: Artistic-2.0 MD5sum: ee104c1824d8dedffb78d40c5a3848e5 NeedsCompilation: no Title: R based tk widgets Description: Widgets to provide user interfaces. tcltk should have been installed for the widgets to run. biocViews: Infrastructure Author: J. Zhang Maintainer: J. Zhang source.ver: src/contrib/tkWidgets_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/tkWidgets_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/tkWidgets_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/tkWidgets_1.38.0.tgz vignettes: vignettes/tkWidgets/inst/doc/importWizard.pdf, vignettes/tkWidgets/inst/doc/tkWidgets.pdf vignetteTitles: tkWidgets importWizard, tkWidgets contents hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tkWidgets/inst/doc/importWizard.R, vignettes/tkWidgets/inst/doc/tkWidgets.R dependsOnMe: oneChannelGUI importsMe: Mfuzz, OLINgui suggestsMe: affy, affyQCReport, annotate, Biobase, genefilter, marray Package: topGO Version: 2.12.0 Depends: R (>= 2.10.0), methods, graph (>= 1.14.0), Biobase (>= 2.0.0), GO.db (>= 2.3.0), AnnotationDbi (>= 1.7.19), SparseM (>= 0.73) Imports: methods, graph, Biobase, SparseM, AnnotationDbi, lattice Suggests: ALL, hgu95av2.db, hgu133a.db, genefilter, xtable, multtest, Rgraphviz, globaltest License: LGPL MD5sum: 3e7c3a4bf1fc7518dac695d42ac65037 NeedsCompilation: no Title: topGO: Enrichment analysis for Gene Ontology Description: topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied. biocViews: Microarray,Bioinformatics,Visualization Author: Adrian Alexa, Jorg Rahnenfuhrer Maintainer: Adrian Alexa source.ver: src/contrib/topGO_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/topGO_2.12.0.zip win64.binary.ver: bin/windows64/contrib/2.16/topGO_2.12.0.zip mac.binary.ver: bin/macosx/contrib/2.16/topGO_2.12.0.tgz vignettes: vignettes/topGO/inst/doc/topGO_classes_v3.pdf, vignettes/topGO/inst/doc/topGO.pdf vignetteTitles: topGO_classes_v3.pdf, topGO hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/topGO/inst/doc/topGO.R dependsOnMe: RNAither suggestsMe: Ringo Package: TransView Version: 1.4.5 Depends: methods,GenomicRanges Imports: Rsamtools,zlibbioc,gplots,IRanges LinkingTo: Rsamtools Suggests: RUnit,pasillaBamSubset License: GPL-3 Archs: i386, x64 MD5sum: 9c35ee122edb77be19eb6fdd23ea64d0 NeedsCompilation: yes Title: Read density map construction and accession. Visualization of ChIPSeq and RNASeq data sets. Description: This package provides efficient tools to generate, access and display read densities of sequencing based data sets such as from RNA-Seq and ChIP-Seq. biocViews: Bioinformatics,DNAMethylation,GeneExpression,Transcription, Microarray,Sequencing,HighThroughputSequencing,ChIPseq,RNAseq, Methylseq,DataImport,Visualization,Clustering,MultipleComparisons Author: Julius Muller Maintainer: Julius Muller URL: http://bioconductor.org/packages/release/bioc/html/TransView.html source.ver: src/contrib/TransView_1.4.5.tar.gz win.binary.ver: bin/windows/contrib/2.16/TransView_1.4.5.zip win64.binary.ver: bin/windows64/contrib/2.16/TransView_1.4.5.zip mac.binary.ver: bin/macosx/contrib/2.16/TransView_1.4.5.tgz vignettes: vignettes/TransView/inst/doc/TransView.pdf vignetteTitles: An introduction to TransView hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TransView/inst/doc/TransView.R Package: triform Version: 1.2.0 Depends: R (>= 2.11.0), IRanges, yaml Imports: IRanges, yaml, BiocGenerics Suggests: RUnit License: GPL-2 MD5sum: 8dcf4b38e7b77f68bb6c4707de601a47 NeedsCompilation: no Title: Triform finds enriched regions (peaks) in transcription factor ChIP-sequencing data Description: The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics. biocViews: Sequencing, ChIPseq Author: Karl Kornacker Developer [aut], Tony Håndstad Developer [aut, cre] Maintainer: Tony Håndstad Developer source.ver: src/contrib/triform_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/triform_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/triform_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/triform_1.2.0.tgz vignettes: vignettes/triform/inst/doc/triform.pdf vignetteTitles: Triform users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/triform/inst/doc/triform.R Package: trigger Version: 1.6.0 Depends: R (>= 2.14.0), corpcor, qtl Imports: qvalue, methods, graphics, sva License: GPL-3 Archs: i386, x64 MD5sum: 77eef48eef1c5a6337b9f58f4f38096d NeedsCompilation: yes Title: Transcriptional Regulatory Inference from Genetics of Gene ExpRession Description: This R package provides tools for the statistical analysis of integrative genomic data that involve some combination of: genotypes, high-dimensional intermediate traits (e.g., gene expression, protein abundance), and higher-order traits (phenotypes). The package includes functions to: (1) construct global linkage maps between genetic markers and gene expression; (2) analyze multiple-locus linkage (epistasis) for gene expression; (3) quantify the proportion of genome-wide variation explained by each locus and identify eQTL hotspots; (4) estimate pair-wise causal gene regulatory probabilities and construct gene regulatory networks; and (5) identify causal genes for a quantitative trait of interest. biocViews: GeneExpression, SNP, GeneticVariability, Microarray, Genetics Author: Lin S. Chen , Dipen P. Sangurdekar and John D. Storey Maintainer: John D. Storey source.ver: src/contrib/trigger_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/trigger_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/trigger_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/trigger_1.6.0.tgz vignettes: vignettes/trigger/inst/doc/net50.pdf, vignettes/trigger/inst/doc/trigger.pdf vignetteTitles: net50.pdf, Trigger Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/trigger/inst/doc/trigger.R Package: triplex Version: 1.0.10 Depends: R (>= 2.15.0), Biostrings (>= 2.26.0) Imports: methods, grid, Biostrings, GenomicRanges LinkingTo: Biostrings, IRanges Suggests: rgl (>= 0.93.932), BSgenome.Celegans.UCSC.ce10, rtracklayer, GenomeGraphs License: BSD Archs: i386, x64 MD5sum: 37419b7889d32eb75b70a19284bc9fb1 NeedsCompilation: yes Title: Search and visualize intramolecular triplex-forming sequences in DNA Description: This package provides functions for identification and visualization of potential intramolecular triplex patterns in DNA sequence. The main functionality is to detect the positions of subsequences capable of folding into an intramolecular triplex (H-DNA) in a much larger sequence. The potential H-DNA (triplexes) should be made of as many cannonical nucleotide triplets as possible. The package includes visualization showing the exact base-pairing in 1D, 2D or 3D. biocViews: SequenceMatching, GeneRegulation Author: Jiri Hon, Matej Lexa, Tomas Martinek and Kamil Rajdl with contributions from Daniel Kopecek Maintainer: Jiri Hon URL: http://www.fi.muni.cz/~lexa/triplex/ source.ver: src/contrib/triplex_1.0.10.tar.gz win.binary.ver: bin/windows/contrib/2.16/triplex_1.0.10.zip win64.binary.ver: bin/windows64/contrib/2.16/triplex_1.0.10.zip mac.binary.ver: bin/macosx/contrib/2.16/triplex_1.0.10.tgz vignettes: vignettes/triplex/inst/doc/triplex.pdf vignetteTitles: Triplex User Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/triplex/inst/doc/triplex.R Package: tspair Version: 1.18.0 Depends: R (>= 2.10), Biobase (>= 2.4.0) License: GPL-2 Archs: i386, x64 MD5sum: ca79d67753f17b38b6067c4dd5f11b2c NeedsCompilation: yes Title: Top Scoring Pairs for Microarray Classification Description: These functions calculate the pair of genes that show the maximum difference in ranking between two user specified groups. This "top scoring pair" maximizes the average of sensitivity and specificity over all rank based classifiers using a pair of genes in the data set. The advantage of classifying samples based on only the relative rank of a pair of genes is (a) the classifiers are much simpler and often more interpretable than more complicated classification schemes and (b) if arrays can be classified using only a pair of genes, PCR based tests could be used for classification of samples. See the references for the tspcalc() function for references regarding TSP classifiers. biocViews: Microarray, Bioinformatics Author: Jeffrey T. Leek Maintainer: Jeffrey T. Leek source.ver: src/contrib/tspair_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/tspair_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/tspair_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/tspair_1.18.0.tgz vignettes: vignettes/tspair/inst/doc/tsp1.pdf, vignettes/tspair/inst/doc/tsp.pdf vignetteTitles: tsp1.pdf, tspTutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tspair/inst/doc/tsp.R dependsOnMe: stepwiseCM Package: TSSi Version: 1.6.0 Depends: R (>= 2.13.2), BiocGenerics (>= 0.3.2) Imports: BiocGenerics, methods, Hmisc, minqa, stats, Biobase (>= 0.3.2), plyr, IRanges Suggests: rtracklayer Enhances: multicore License: GPL-3 Archs: i386, x64 MD5sum: 2c95d68c821ed1b1ec0df2f6b11f235b NeedsCompilation: yes Title: Transcription Start Site Identification Description: Identify and normalize transcription start sites in high-throughput sequencing data. biocViews: Sequencing, HighThroughputSequencing, RNAseq, Genetics, Preprocessing Author: Clemens Kreutz, Julian Gehring Maintainer: Julian Gehring URL: http://julian-gehring.github.com/TSSi/ source.ver: src/contrib/TSSi_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/TSSi_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/TSSi_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/TSSi_1.6.0.tgz vignettes: vignettes/TSSi/inst/doc/TSSi.pdf vignetteTitles: Introduction to the TSSi package: Identification of Transcription Start Sites hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/TSSi/inst/doc/TSSi.R Package: TurboNorm Version: 1.8.0 Depends: R (>= 2.12.0), convert, limma (>= 1.7.0), marray Imports: stats, grDevices, affy, lattice Suggests: affydata, affy, lattice License: LGPL Archs: i386, x64 MD5sum: 9229b3eb7731c613c9610bf50f2b66e7 NeedsCompilation: yes Title: A fast scatterplot smoother suitable for microarray normalization Description: A fast scatterplot smoother based on B-splines with second-order difference penalty. Functions for microarray normalization of single-colour data i.e. Affymetrix/Illumina and two-colour data supplied as marray MarrayRaw-objects or limma RGList-objects are available. biocViews: Microarray, OneChannel, TwoChannel, Preprocessing, DNAMethylation, CpGIsland Author: Maarten van Iterson and Chantal van Leeuwen Maintainer: Maarten van Iterson URL: http://www.humgen.nl/MicroarrayAnalysisGroup.html source.ver: src/contrib/TurboNorm_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/TurboNorm_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/TurboNorm_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/TurboNorm_1.8.0.tgz vignettes: vignettes/TurboNorm/inst/doc/turbonorm.pdf vignetteTitles: TurboNorm Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TurboNorm/inst/doc/turbonorm.R Package: tweeDEseq Version: 1.6.2 Depends: R (>= 2.12.0) Imports: MASS, limma, edgeR, parallel, cqn Suggests: tweeDEseqCountData, xtable License: GPL (>= 2) Archs: i386, x64 MD5sum: bdb529c7c0cd4bd3cb985139a905a9ae NeedsCompilation: yes Title: RNA-seq data analysis using the Poisson-Tweedie family of distributions Description: Differential expression analysis of RNA-seq using the Poisson-Tweedie family of distributions. biocViews: Statistics, DifferentialExpression, HighThroughputSequencing, RNAseq Author: Juan R Gonzalez and Mikel Esnaola (with contributions from Robert Castelo ) Maintainer: Juan R Gonzalez URL: http://www.creal.cat/jrgonzalez/software.htm source.ver: src/contrib/tweeDEseq_1.6.2.tar.gz win.binary.ver: bin/windows/contrib/2.16/tweeDEseq_1.6.2.zip win64.binary.ver: bin/windows64/contrib/2.16/tweeDEseq_1.6.2.zip mac.binary.ver: bin/macosx/contrib/2.16/tweeDEseq_1.6.2.tgz vignettes: vignettes/tweeDEseq/inst/doc/tweeDEseq.pdf vignetteTitles: tweeDEseq: analysis of RNA-seq data using the Poisson-Tweedie family of distributions hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tweeDEseq/inst/doc/tweeDEseq.R Package: twilight Version: 1.36.0 Depends: R (>= 2.10), splines (>= 2.2.0), stats (>= 2.2.0), Biobase(>= 1.12.0) Imports: Biobase, graphics, grDevices, stats Suggests: golubEsets (>= 1.4.2), vsn (>= 1.7.2) License: GPL (>= 2) Archs: i386, x64 MD5sum: ed3f40dcf66bb5338322c5f4338b6478 NeedsCompilation: yes Title: Estimation of local false discovery rate Description: In a typical microarray setting with gene expression data observed under two conditions, the local false discovery rate describes the probability that a gene is not differentially expressed between the two conditions given its corrresponding observed score or p-value level. The resulting curve of p-values versus local false discovery rate offers an insight into the twilight zone between clear differential and clear non-differential gene expression. Package 'twilight' contains two main functions: Function twilight.pval performs a two-condition test on differences in means for a given input matrix or expression set and computes permutation based p-values. Function twilight performs a stochastic downhill search to estimate local false discovery rates and effect size distributions. The package further provides means to filter for permutations that describe the null distribution correctly. Using filtered permutations, the influence of hidden confounders could be diminished. biocViews: Microarray, Bioinformatics, DifferentialExpression, MultipleComparisons Author: Stefanie Scheid Maintainer: Stefanie Scheid URL: http://compdiag.molgen.mpg.de/software/twilight.shtml source.ver: src/contrib/twilight_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/twilight_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/twilight_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/twilight_1.36.0.tgz vignettes: vignettes/twilight/inst/doc/bcb_logo.pdf, vignettes/twilight/inst/doc/tr_2004_01.pdf vignetteTitles: bcb_logo.pdf, Estimation of Local False Discovery Rates hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/twilight/inst/doc/tr_2004_01.R dependsOnMe: OrderedList importsMe: OrderedList Package: TypeInfo Version: 1.26.0 Depends: methods Suggests: Biobase License: BSD MD5sum: 5de8bb833d2a0d14e1321fbd3bc7c789 NeedsCompilation: no Title: Optional Type Specification Prototype Description: A prototype for a mechanism for specifying the types of parameters and the return value for an R function. This is meta-information that can be used to generate stubs for servers and various interfaces to these functions. Additionally, the arguments in a call to a typed function can be validated using the type specifications. We allow types to be specified as either i) by class name using either inheritance - is(x, className), or strict instance of - class(x) %in% className, or ii) a dynamic test given as an R expression which is evaluated at run-time. More precise information and interesting tests can be done via ii), but it is harder to use this information as meta-data as it requires more effort to interpret it and it is of course run-time information. It is typically more meaningful. biocViews: Infrastructure Author: Duncan Temple Lang Robert Gentleman () Maintainer: Duncan Temple Lang source.ver: src/contrib/TypeInfo_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/TypeInfo_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/TypeInfo_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/TypeInfo_1.26.0.tgz vignettes: vignettes/TypeInfo/inst/doc/TypeInfoNews.pdf vignetteTitles: TypeInfo R News hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TypeInfo/inst/doc/TypeInfoNews.R htmlDocs: vignettes/TypeInfo/inst/doc/outline.html htmlTitles: "outline.html" dependsOnMe: RWebServices Package: UniProt.ws Version: 2.0.1 Depends: RSQLite, RCurl, methods, utils Imports: BiocGenerics, AnnotationDbi Suggests: RUnit License: Artistic License 2.0 MD5sum: 01dbd574a7d5bf1279a9f93880e0484b NeedsCompilation: no Title: R Interface to UniProt Web Services Description: A collection of functions for retrieving, processing and repackaging the Uniprot web services. biocViews: Annotation, Infrastructure Author: Marc Carlson Maintainer: Marc Carlson source.ver: src/contrib/UniProt.ws_2.0.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/UniProt.ws_2.0.1.zip win64.binary.ver: bin/windows64/contrib/2.16/UniProt.ws_2.0.1.zip mac.binary.ver: bin/macosx/contrib/2.16/UniProt.ws_2.0.1.tgz vignettes: vignettes/UniProt.ws/inst/doc/UniProt.ws.pdf vignetteTitles: UniProt.ws: A package for retrieving data from the UniProt web service hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/UniProt.ws/inst/doc/UniProt.ws.R Package: VanillaICE Version: 1.22.0 Depends: R (>= 2.14.0) Imports: stats, utils, methods, Biobase, oligoClasses (>= 1.21.12),lattice, IRanges (>= 1.13.22), grid, msm, iterators, foreach, GenomicRanges, matrixStats Suggests: genomewidesnp6Crlmm (>= 1.0.7), hapmapsnp6, RColorBrewer, genefilter, RSQLite, foreach, RUnit, pd.mapping50k.hind240, SNPchip (>= 2.5.7), doSNOW Enhances: DNAcopy, crlmm (>= 1.17.14) License: LGPL-2 Archs: i386, x64 MD5sum: 832f338dce89e0ad6a39aa79842f3464 NeedsCompilation: yes Title: A Hidden Markov Model for high throughput genotyping arrays Description: Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays biocViews: Bioinformatics, CopyNumberVariants, SNP, GeneticVariability, Visualization Author: Robert Scharpf , Kevin Scharpf, and Ingo Ruczinski Maintainer: Robert Scharpf source.ver: src/contrib/VanillaICE_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/VanillaICE_1.22.0.zip win64.binary.ver: bin/windows64/contrib/2.16/VanillaICE_1.22.0.zip mac.binary.ver: bin/macosx/contrib/2.16/VanillaICE_1.22.0.tgz vignettes: vignettes/VanillaICE/inst/doc/crlmmDownstream.pdf, vignettes/VanillaICE/inst/doc/VanillaICE.pdf vignetteTitles: crlmmDownstream, VanillaICE Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VanillaICE/inst/doc/crlmmDownstream.R, vignettes/VanillaICE/inst/doc/VanillaICE.R importsMe: MinimumDistance suggestsMe: oligoClasses Package: VariantAnnotation Version: 1.6.8 Depends: R (>= 2.8.0), methods, BiocGenerics, GenomicRanges (>= 1.11.29), Rsamtools (>= 1.11.26), IRanges (>= 1.17.4) Imports: methods, BiocGenerics, IRanges, Biostrings, Biobase, Rsamtools, AnnotationDbi (>= 1.17.11), zlibbioc, BSgenome, GenomicFeatures (>= 1.9.35), DBI, utils LinkingTo: IRanges, Biostrings, Rsamtools Suggests: RUnit, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, SNPlocs.Hsapiens.dbSNP.20110815, SNPlocs.Hsapiens.dbSNP.20101109, SIFT.Hsapiens.dbSNP132, PolyPhen.Hsapiens.dbSNP131, snpStats, ggplot2 License: Artistic-2.0 Archs: i386, x64 MD5sum: f3cec2ea32ae8e6d7ff775c33508c074 NeedsCompilation: yes Title: Annotation of Genetic Variants Description: Annotate variants, compute amino acid coding changes, predict coding outcomes biocViews: DataImport, Sequencing, HighThroughputSequencing, SNP, Annotation, Genetics, Homo_sapiens Author: Valerie Obenchain, Martin Morgan, Michael Lawrence with contributions from Stephanie Gogarten. Maintainer: Valerie Obenchain source.ver: src/contrib/VariantAnnotation_1.6.8.tar.gz win.binary.ver: bin/windows/contrib/2.16/VariantAnnotation_1.6.8.zip win64.binary.ver: bin/windows64/contrib/2.16/VariantAnnotation_1.6.8.zip mac.binary.ver: bin/macosx/contrib/2.16/VariantAnnotation_1.6.8.tgz vignettes: vignettes/VariantAnnotation/inst/doc/filterVcf.pdf, vignettes/VariantAnnotation/inst/doc/VariantAnnotation.pdf vignetteTitles: filterVcf Overview, Introduction to VariantAnnotation hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VariantAnnotation/inst/doc/filterVcf.R, vignettes/VariantAnnotation/inst/doc/VariantAnnotation.R dependsOnMe: ensemblVEP, VariantTools importsMe: FunciSNP, ggbio, GGtools, gmapR, HTSeqGenie, R453Plus1Toolbox, VariantTools suggestsMe: GenomicRanges, gmapR, GWASTools Package: VariantTools Version: 1.2.2 Depends: IRanges (>= 1.17.10), GenomicRanges (>= 1.9.52), VariantAnnotation (>= 1.3.20), methods Imports: IRanges, Rsamtools (>= 1.11.10), GenomicRanges, BiocGenerics, Biostrings, parallel, gmapR (>= 1.1.16), GenomicFeatures, VariantAnnotation, methods, RBGL, graph, Matrix, rtracklayer Suggests: RUnit, LungCancerLines (>= 0.0.6) License: Artistic-2.0 MD5sum: daf5f1dc4f87f07cee1d764cf8339c3a NeedsCompilation: no Title: Tools for Working with Genetic Variants Description: Tools for detecting, filtering, calling, comparing and plotting variants. biocViews: Genetics, GeneticVariability, HighThroughputSequencing Author: Michael Lawrence, Jeremiah Degenhardt, Robert Gentleman Maintainer: Michael Lawrence source.ver: src/contrib/VariantTools_1.2.2.tar.gz vignettes: vignettes/VariantTools/inst/doc/VariantTools.pdf vignetteTitles: Introduction to VariantTools hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VariantTools/inst/doc/VariantTools.R importsMe: HTSeqGenie Package: vbmp Version: 1.28.0 Depends: R (>= 2.10) Suggests: Biobase (>= 2.5.5), statmod License: GPL (>= 2) MD5sum: 87fc0379877ddcc4bdae719434808a02 NeedsCompilation: no Title: Variational Bayesian Multinomial Probit Regression Description: Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination. biocViews: Bioinformatics,Classification Author: Nicola Lama , Mark Girolami Maintainer: Nicola Lama URL: http://bioinformatics.oxfordjournals.org/cgi/content/short/btm535v1 source.ver: src/contrib/vbmp_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/vbmp_1.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/vbmp_1.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/vbmp_1.28.0.tgz vignettes: vignettes/vbmp/inst/doc/vbmp.pdf vignetteTitles: vbmp Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/vbmp/inst/doc/vbmp.R Package: Vega Version: 1.8.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: 02b3d75b679de328f6c57ccb10adf36b NeedsCompilation: yes Title: An R package for copy number data segmentation Description: Vega (Variational Estimator for Genomic Aberrations) is an algorithm that adapts a very popular variational model (Mumford and Shah) used in image segmentation so that chromosomal aberrant regions can be efficiently detected. biocViews: aCGH, CopyNumberVariants Author: Sandro Morganella Maintainer: Sandro Morganella source.ver: src/contrib/Vega_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/Vega_1.8.0.zip win64.binary.ver: bin/windows64/contrib/2.16/Vega_1.8.0.zip mac.binary.ver: bin/macosx/contrib/2.16/Vega_1.8.0.tgz vignettes: vignettes/Vega/inst/doc/Vega.pdf vignetteTitles: Vega hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Vega/inst/doc/Vega.R Package: VegaMC Version: 2.7.0 Depends: R (>= 2.10.0), biomaRt, Biobase, genoset Imports: methods License: GPL-2 Archs: i386, x64 MD5sum: 390635bdd37c4e14c03df326c24cd188 NeedsCompilation: yes Title: VegaMC: A Package Implementing a Variational Piecewise Smooth Model for Identification of Driver Chromosomal Imbalances in Cancer Description: This package enables the detection of driver chromosomal imbalances including loss of heterozygosity (LOH) from array comparative genomic hybridization (aCGH) data. VegaMC performs a joint segmentation of a dataset and uses a statistical framework to distinguish between driver and passenger mutation. VegaMC has been implemented so that it can be immediately integrated with the output produced by PennCNV tool. In addition, VegaMC produces in output two web pages that allows a rapid navigation between both the detected regions and the altered genes. In the web page that summarizes the altered genes, the link to the respective Ensembl gene web page is reported. biocViews: Bioinformatics, aCGH, CopyNumberVariants Author: S. Morganella and M. Ceccarelli Maintainer: Sandro Morganella source.ver: src/contrib/VegaMC_2.7.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/VegaMC_2.7.0.zip win64.binary.ver: bin/windows64/contrib/2.16/VegaMC_2.7.0.zip mac.binary.ver: bin/macosx/contrib/2.16/VegaMC_2.7.0.tgz vignettes: vignettes/VegaMC/inst/doc/VegaMC.pdf vignetteTitles: VegaMC hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VegaMC/inst/doc/VegaMC.R Package: virtualArray Version: 1.4.1 Depends: R (>= 2.15.0), BiocGenerics, methods, plyr, preprocessCore Imports: affy, affyPLM, AnnotationDbi, Biobase, gcrma, GEOquery, graphics, methods, reshape2, stats, utils, tseries, outliers Suggests: affydata, plier, limma, lumi, org.Hs.eg.db Enhances: multicore,BiocParallel License: GPL-3 MD5sum: fd70eb4b8bc2ee55343f9e08ded231fd NeedsCompilation: no Title: Build virtual array from different microarray platforms Description: This package permits the user to combine raw data of different microarray platforms into one virtual array. It consists of several functions that act subsequently in a semi-automatic way. Doing as much of the data combination and letting the user concentrate on analysing the resulting virtual array. biocViews: Microarray, OneChannel, DataImport, Preprocessing, Bioinformatics, MultipleComparisons Author: Andreas Heider Maintainer: Andreas Heider source.ver: src/contrib/virtualArray_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/2.16/virtualArray_1.4.1.zip win64.binary.ver: bin/windows64/contrib/2.16/virtualArray_1.4.1.zip mac.binary.ver: bin/macosx/contrib/2.16/virtualArray_1.4.1.tgz vignettes: vignettes/virtualArray/inst/doc/virtualArray-016.pdf, vignettes/virtualArray/inst/doc/virtualArray.pdf vignetteTitles: virtualArray-016.pdf, virtualArray Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/virtualArray/inst/doc/virtualArray.R Package: vsn Version: 3.28.0 Depends: R (>= 2.10), Biobase (>= 2.5.5) Imports: methods, affy (>= 1.23.4), limma, lattice Suggests: affydata, hgu95av2cdf License: Artistic-2.0 Archs: i386, x64 MD5sum: eebf6f288547a22cc81d09c1a65a7c60 NeedsCompilation: yes Title: Variance stabilization and calibration for microarray data Description: The package implements a method for normalising microarray intensities, both between colours within array, and between arrays. The method uses a robust variant of the maximum-likelihood estimator for the stochastic model of microarray data described in the references (see vignette). The model incorporates data calibration (a.k.a. normalization), a model for the dependence of the variance on the mean intensity, and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription. biocViews: Microarray, OneChannel, TwoChannel, Preprocessing Author: Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth. Maintainer: Wolfgang Huber URL: http://www.r-project.org, http://www.ebi.ac.uk/huber source.ver: src/contrib/vsn_3.28.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/vsn_3.28.0.zip win64.binary.ver: bin/windows64/contrib/2.16/vsn_3.28.0.zip mac.binary.ver: bin/macosx/contrib/2.16/vsn_3.28.0.tgz vignettes: vignettes/vsn/inst/doc/convergence2.pdf, vignettes/vsn/inst/doc/likelihoodcomputations.pdf, vignettes/vsn/inst/doc/vsn.pdf vignetteTitles: Verifying and assessing the performance with simulated data, Likelihood Calculations for vsn, Introduction to vsn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/vsn/inst/doc/convergence2.R, vignettes/vsn/inst/doc/likelihoodcomputations.R, vignettes/vsn/inst/doc/vsn.R dependsOnMe: affyPara, cellHTS2, LVSmiRNA, MmPalateMiRNA, webbioc importsMe: arrayQualityMetrics, imageHTS, MSnbase, pvca, Ringo, tilingArray suggestsMe: adSplit, Agi4x44PreProcess, beadarray, BiocCaseStudies, cellHTS, DESeq, DESeq2, GlobalAncova, globaltest, limma, lumi, twilight Package: wateRmelon Version: 1.0.3 Depends: R (>= 2.10), limma, methods, matrixStats, methylumi, lumi, IlluminaHumanMethylation450k.db, ROC Suggests: RPMM Enhances: minfi, methylumi, IMA License: GPL-3 MD5sum: 7d2b682514879358351ca9a3af68ae81 NeedsCompilation: no Title: Illumina 450 methylation array normalization and metrics Description: 15 flavours of betas and three performance metrics, with methods for objects produced by methylumi, minfi and IMA packages. biocViews: DNAMethylation, Microarray, TwoChannel, Preprocessing, QualityControl Author: Leonard C Schalkwyk, Ruth Pidsley, Chloe CY Wong, with functions contributed by Nizar Touleimat, Matthieu Defrance, Andrew Teschendorff, Jovana Maksimovic Maintainer: Leo source.ver: src/contrib/wateRmelon_1.0.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/wateRmelon_1.0.3.zip win64.binary.ver: bin/windows64/contrib/2.16/wateRmelon_1.0.3.zip mac.binary.ver: bin/macosx/contrib/2.16/wateRmelon_1.0.3.tgz vignettes: vignettes/wateRmelon/inst/doc/wateRmelon.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/wateRmelon/inst/doc/wateRmelon.R Package: waveTiling Version: 1.2.0 Depends: oligo, oligoClasses, Biobase, Biostrings, GenomeGraphs Imports: methods, affy, preprocessCore, GenomicRanges, waveslim, IRanges Suggests: BSgenome, BSgenome.Athaliana.TAIR.TAIR9, waveTilingData, pd.atdschip.tiling, TxDb.Athaliana.BioMart.plantsmart12 License: GPL (>=2) Archs: i386, x64 MD5sum: 7d3a86f23070e1ceb6d32ad9e1ff6ddb NeedsCompilation: yes Title: Wavelet-Based Models for Tiling Array Transcriptome Analysis Description: This package is designed to conduct transcriptome analysis for tiling arrays based on fast wavelet-based functional models. biocViews: MicroArray, DifferentialExpression, TimeCourse, GeneExpression Author: Kristof De Beuf , Peter Pipelers and Lieven Clement Maintainer: Kristof De Beuf URL: https://r-forge.r-project.org/projects/wavetiling/ source.ver: src/contrib/waveTiling_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/waveTiling_1.2.0.zip win64.binary.ver: bin/windows64/contrib/2.16/waveTiling_1.2.0.zip mac.binary.ver: bin/macosx/contrib/2.16/waveTiling_1.2.0.tgz vignettes: vignettes/waveTiling/inst/doc/waveTiling-vignette.pdf vignetteTitles: The waveTiling package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/waveTiling/inst/doc/waveTiling-vignette.R Package: weaver Version: 1.26.0 Depends: R (>= 2.5.0), digest, tools, utils, codetools Suggests: codetools License: GPL-2 MD5sum: e02b03584a628181041ebeab245aae9b NeedsCompilation: no Title: Tools and extensions for processing Sweave documents Description: This package provides enhancements on the Sweave() function in the base package. In particular a facility for caching code chunk results is included. biocViews: Infrastructure Author: Seth Falcon Maintainer: Seth Falcon source.ver: src/contrib/weaver_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/weaver_1.26.0.zip win64.binary.ver: bin/windows64/contrib/2.16/weaver_1.26.0.zip mac.binary.ver: bin/macosx/contrib/2.16/weaver_1.26.0.tgz vignettes: vignettes/weaver/inst/doc/weaver_howTo.pdf vignetteTitles: Using weaver to process Sweave documents hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/weaver/inst/doc/weaver_howTo.R suggestsMe: BiocCaseStudies Package: webbioc Version: 1.32.0 Depends: R (>= 1.8.0), Biobase, affy, multtest, annaffy, vsn, gcrma, qvalue Imports: multtest, qvalue, stats, utils, BiocInstaller License: GPL (>= 2) MD5sum: 848231d3cdc3f20bb458283f3a3e1799 NeedsCompilation: no Title: Bioconductor Web Interface Description: An integrated web interface for doing microarray analysis using several of the Bioconductor packages. It is intended to be deployed as a centralized bioinformatics resource for use by many users. (Currently only Affymetrix oligonucleotide analysis is supported.) biocViews: Infrastructure, Microarray, OneChannel, DifferentialExpression Author: Colin A. Smith Maintainer: Colin A. Smith URL: http://www.bioconductor.org/ SystemRequirements: Unix, Perl (>= 5.6.0), Netpbm source.ver: src/contrib/webbioc_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/webbioc_1.32.0.zip win64.binary.ver: bin/windows64/contrib/2.16/webbioc_1.32.0.zip mac.binary.ver: bin/macosx/contrib/2.16/webbioc_1.32.0.tgz vignettes: vignettes/webbioc/inst/doc/demoscript.pdf, vignettes/webbioc/inst/doc/webbioc.pdf vignetteTitles: webbioc Demo Script, webbioc Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/webbioc/inst/doc/demoscript.R, vignettes/webbioc/inst/doc/webbioc.R Package: widgetTools Version: 1.38.0 Depends: R (>= 2.4.0), methods, utils, tcltk Suggests: Biobase License: LGPL MD5sum: 0616d66668bf8bd6937bc8175126104f NeedsCompilation: no Title: Creates an interactive tcltk widget Description: This packages contains tools to support the construction of tcltk widgets biocViews: Infrastructure Author: Jianhua Zhang Maintainer: Jianhua Zhang source.ver: src/contrib/widgetTools_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/widgetTools_1.38.0.zip win64.binary.ver: bin/windows64/contrib/2.16/widgetTools_1.38.0.zip mac.binary.ver: bin/macosx/contrib/2.16/widgetTools_1.38.0.tgz vignettes: vignettes/widgetTools/inst/doc/widget.pdf, vignettes/widgetTools/inst/doc/widgetTools.pdf vignetteTitles: widget.pdf, widgetTools Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/widgetTools/inst/doc/widgetTools.R dependsOnMe: tkWidgets importsMe: OLINgui suggestsMe: affy Package: xcms Version: 1.36.0 Depends: R (>= 2.14.0), methods, mzR (>= 1.1.6), BiocGenerics, Biobase Suggests: faahKO, msdata, ncdf, multtest, rgl, MassSpecWavelet (>= 1.5.2), RANN, RUnit Enhances: Rgraphviz, KEGGSOAP, Rmpi License: GPL (>= 2) Archs: i386, x64 MD5sum: d1ae0eaa89ce543c0187840667090e3a NeedsCompilation: yes Title: LC/MS and GC/MS Data Analysis Description: Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling. biocViews: MassSpectrometry, Metabolomics Author: Colin A. Smith , Ralf Tautenhahn , Steffen Neumann , Paul Benton Maintainer: Ralf Tautenhahn URL: http://metlin.scripps.edu/download/ source.ver: src/contrib/xcms_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/xcms_1.36.0.zip win64.binary.ver: bin/windows64/contrib/2.16/xcms_1.36.0.zip mac.binary.ver: bin/macosx/contrib/2.16/xcms_1.36.0.tgz vignettes: vignettes/xcms/inst/doc/FlowChart.pdf, vignettes/xcms/inst/doc/xcmsDirect.pdf, vignettes/xcms/inst/doc/xcmsInstall.pdf, vignettes/xcms/inst/doc/xcmsMSn.pdf, vignettes/xcms/inst/doc/xcmsPreprocess.pdf vignetteTitles: FlowChart.pdf, Grouping FTICR-MS data with xcms, Installation Instructions for xcms, Processing Tandem-MS and MS$^n$ data with xcms, LC/MS Preprocessing and Analysis with xcms hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/xcms/inst/doc/xcmsDirect.R, vignettes/xcms/inst/doc/xcmsInstall.R, vignettes/xcms/inst/doc/xcmsMSn.R, vignettes/xcms/inst/doc/xcmsPreprocess.R dependsOnMe: CAMERA, flagme importsMe: CAMERA, Risa suggestsMe: MassSpecWavelet Package: XDE Version: 2.6.0 Depends: R (>= 2.10.0), Biobase (>= 2.5.5), methods, graphics Imports: Biobase, BiocGenerics, genefilter, graphics, grDevices, gtools, MergeMaid, methods, stats, utils, mvtnorm Suggests: siggenes, genefilter, MASS, RColorBrewer, GeneMeta, RUnit Enhances: coda License: LGPL-2 Archs: i386, x64 MD5sum: a40a305dfe7eb3322fdf1a7be3d23895 NeedsCompilation: yes Title: XDE: a Bayesian hierarchical model for cross-study analysis of differential gene expression Description: Multi-level model for cross-study detection of differential gene expression. biocViews: Microarray, Bioinformatics, DifferentialExpression Author: R.B. Scharpf, G. Parmigiani, A.B. Nobel, and H. Tjelmeland Maintainer: Robert Scharpf source.ver: src/contrib/XDE_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/XDE_2.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/XDE_2.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/XDE_2.6.0.tgz vignettes: vignettes/XDE/inst/doc/XdeParameterClass.pdf, vignettes/XDE/inst/doc/XDE.pdf vignetteTitles: XdeParameterClass Vignette, XDE Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/XDE/inst/doc/XdeParameterClass.R, vignettes/XDE/inst/doc/XDE.R Package: xmapbridge Version: 1.18.0 Depends: R (>= 2.0), methods Suggests: RUnit, RColorBrewer License: LGPL-3 MD5sum: 948d4603d0a3a24bb207c3a63a55c4b8 NeedsCompilation: no Title: Export plotting files to the xmapBridge for visualisation in X:Map Description: xmapBridge can plot graphs in the X:Map genome browser. This package exports plotting files in a suitable format. biocViews: Annotation, ReportWriting, Visualization Author: Tim Yates and Crispin J Miller Maintainer: Tim Yates URL: http://xmap.picr.man.ac.uk, http://www.bioconductor.org source.ver: src/contrib/xmapbridge_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/xmapbridge_1.18.0.zip win64.binary.ver: bin/windows64/contrib/2.16/xmapbridge_1.18.0.zip mac.binary.ver: bin/macosx/contrib/2.16/xmapbridge_1.18.0.tgz vignettes: vignettes/xmapbridge/inst/doc/xmapbridge.pdf vignetteTitles: xmapbridge primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/xmapbridge/inst/doc/xmapbridge.R Package: xmapcore Version: 1.14.0 Depends: R (>= 2.8.0), methods, IRanges Imports: DBI, RMySQL (>= 0.6-0), digest, Biobase Suggests: RUnit License: GPL-2 MD5sum: 639bbcb4c33045eb11ba1dde11aaf91c NeedsCompilation: no Title: Core access to the xmap database (installed separately) Description: xmapcore is deprecated and will not be supported after Bioconductor release 2.10. It has been superceded by a new package 'annmap'. xmapcore allows mapping between genetic features and any available Affymetrix Exon arrays for Homo Sapiens, Mus Musculus, Rattus Norvegicus and Schizosaccharomyces Pombe. biocViews: Annotation, Bioinformatics, Microarray, OneChannel, ReportWriting, Transcription, Visualization Author: Tim Yates Maintainer: Tim Yates URL: http://xmap.picr.man.ac.uk, http://www.bioconductor.org source.ver: src/contrib/xmapcore_1.14.0.tar.gz mac.binary.ver: bin/macosx/contrib/2.16/xmapcore_1.14.0.tgz vignettes: vignettes/xmapcore/inst/doc/cookbook.pdf, vignettes/xmapcore/inst/doc/INSTALL.pdf, vignettes/xmapcore/inst/doc/SplicingIndexExample.pdf, vignettes/xmapcore/inst/doc/xmapcore.pdf vignetteTitles: cookbook.pdf, xmapcore installation instruction, SplicingIndexExample.pdf, xmapcore primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/xmapcore/inst/doc/INSTALL.R, vignettes/xmapcore/inst/doc/xmapcore.R dependsOnMe: rnaSeqMap Package: xps Version: 1.20.3 Depends: R (>= 2.6.0), methods, utils Suggests: tools License: GPL (>= 2.0) Archs: i386 MD5sum: fb0e9172527f43251e090a408264f817 NeedsCompilation: yes Title: Processing and Analysis of Affymetrix Oligonucleotide Arrays including Exon Arrays, Whole Genome Arrays and Plate Arrays Description: The package handles pre-processing, normalization, filtering and analysis of Affymetrix GeneChip expression arrays, including exon arrays (Exon 1.0 ST: core, extended, full probesets), gene arrays (Gene 1.0 ST) and plate arrays on computers with 1 GB RAM only. It imports Affymetrix .CDF, .CLF, .PGF and .CEL as well as annotation files, and computes e.g. RMA, MAS5, FARMS, DFW, FIRMA, tRMA, MAS5-calls, DABG-calls, I/NI-calls. It is an R wrapper to XPS (eXpression Profiling System), which is based on ROOT, an object-oriented framework developed at CERN. Thus, the prior installation of ROOT is a prerequisite for the usage of this package, however, no knowledge of ROOT is required. ROOT is licensed under LGPL and can be downloaded from http://root.cern.ch. biocViews: ExonArray, GeneExpression, Microarray, OneChannel, DataImport, Preprocessing, Transcription, DifferentialExpression Author: Christian Stratowa, Vienna, Austria Maintainer: Christian Stratowa SystemRequirements: root_v5.34.05 - See README file for installation instructions. source.ver: src/contrib/xps_1.20.3.tar.gz win.binary.ver: bin/windows/contrib/2.16/xps_1.20.3.zip win64.binary.ver: bin/windows64/contrib/2.16/xps_1.20.3.zip mac.binary.ver: bin/macosx/contrib/2.16/xps_1.20.3.tgz vignettes: vignettes/xps/inst/doc/APTvsXPS.pdf, vignettes/xps/inst/doc/xpsClasses.pdf, vignettes/xps/inst/doc/xps.pdf, vignettes/xps/inst/doc/xpsPreprocess.pdf vignetteTitles: 3. XPS Vignette: Comparison APT vs XPS, 2. XPS Vignette: Classes, 1. XPS Vignette: Overview, 4. XPS Vignette: Function express() hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/xps/inst/doc/APTvsXPS.R, vignettes/xps/inst/doc/xpsClasses.R, vignettes/xps/inst/doc/xpsPreprocess.R, vignettes/xps/inst/doc/xps.R Package: yaqcaffy Version: 1.20.0 Depends: simpleaffy (>= 2.19.3), methods Imports: stats4 Suggests: MAQCsubsetAFX, affydata, xtable, tcltk2, tcltk License: Artistic-2.0 MD5sum: 88e2447d2fd225faf8174e419ec66933 NeedsCompilation: no Title: Affymetrix expression data quality control and reproducibility analysis Description: Quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets. biocViews: Microarray,OneChannel,QualityControl,ReportWriting Author: Laurent Gatto Maintainer: Laurent Gatto source.ver: src/contrib/yaqcaffy_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/yaqcaffy_1.20.0.zip win64.binary.ver: bin/windows64/contrib/2.16/yaqcaffy_1.20.0.zip mac.binary.ver: bin/macosx/contrib/2.16/yaqcaffy_1.20.0.tgz vignettes: vignettes/yaqcaffy/inst/doc/yaqcaffy.pdf vignetteTitles: yaqcaffy: Affymetrix quality control and MAQC reproducibility hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/yaqcaffy/inst/doc/yaqcaffy.R Package: zlibbioc Version: 1.6.0 License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: c269d858fddc5597455c8148d689ba44 NeedsCompilation: yes Title: An R packaged zlib-1.2.5 Description: This package uses the source code of zlib-1.2.5 to create libraries for systems that do not have these available via other means (most Linux and Mac users should have system-level access to zlib, and no direct need for this package). See the vignette for instructions on use. biocViews: Infrastructure Author: Martin Morgan Maintainer: Bioconductor Package Maintainer URL: http://bioconductor.org/packages/release/bioc/html/Zlibbioc.html source.ver: src/contrib/zlibbioc_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/2.16/zlibbioc_1.6.0.zip win64.binary.ver: bin/windows64/contrib/2.16/zlibbioc_1.6.0.zip mac.binary.ver: bin/macosx/contrib/2.16/zlibbioc_1.6.0.tgz vignettes: vignettes/zlibbioc/inst/doc/UsingZlibbioc.pdf vignetteTitles: Using zlibbioc C libraries hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/zlibbioc/inst/doc/UsingZlibbioc.R dependsOnMe: BitSeq importsMe: affy, affyio, affyPLM, DiffBind, makecdfenv, oligo, QuasR, rhdf5, Rsamtools, rtracklayer, seqbias, ShortRead, Starr, VariantAnnotation