Back to Multiple platform build/check report for BioC 3.21: simplified long |
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This page was generated on 2024-11-28 12:15 -0500 (Thu, 28 Nov 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" | 4748 |
palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences" | 4459 |
lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4398 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 1959/2272 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
singleCellTK 2.17.0 (landing page) Joshua David Campbell
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | ERROR | ERROR | skipped | skipped | |||||||||
To the developers/maintainers of the singleCellTK package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/singleCellTK.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: singleCellTK |
Version: 2.17.0 |
Command: /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings singleCellTK_2.17.0.tar.gz |
StartedAt: 2024-11-28 06:22:57 -0500 (Thu, 28 Nov 2024) |
EndedAt: 2024-11-28 06:39:45 -0500 (Thu, 28 Nov 2024) |
EllapsedTime: 1008.9 seconds |
RetCode: 0 |
Status: OK |
CheckDir: singleCellTK.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:singleCellTK.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings singleCellTK_2.17.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck’ * using R Under development (unstable) (2024-10-21 r87258) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0 GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0 * running under: Ubuntu 24.04.1 LTS * using session charset: UTF-8 * checking for file ‘singleCellTK/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘singleCellTK’ version ‘2.17.0’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib: cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES' INFO Imports includes 79 non-default packages. Importing from so many packages makes the package vulnerable to any of them becoming unavailable. Move as many as possible to Suggests and use conditionally. * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘singleCellTK’ can be installed ... OK * checking installed package size ... INFO installed size is 5.6Mb sub-directories of 1Mb or more: shiny 2.3Mb * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... NOTE License stub is invalid DCF. * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking whether startup messages can be suppressed ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... NOTE Found the following Rd file(s) with Rd \link{} targets missing package anchors: dedupRowNames.Rd: SingleCellExperiment-class detectCellOutlier.Rd: colData diffAbundanceFET.Rd: colData downSampleCells.Rd: SingleCellExperiment-class downSampleDepth.Rd: SingleCellExperiment-class featureIndex.Rd: SummarizedExperiment-class, SingleCellExperiment-class getBiomarker.Rd: SingleCellExperiment-class getDEGTopTable.Rd: SingleCellExperiment-class getEnrichRResult.Rd: SingleCellExperiment-class getFindMarkerTopTable.Rd: SingleCellExperiment-class getGenesetNamesFromCollection.Rd: SingleCellExperiment-class getPathwayResultNames.Rd: SingleCellExperiment-class getSampleSummaryStatsTable.Rd: SingleCellExperiment-class, assay, colData getSoupX.Rd: SingleCellExperiment-class getTSCANResults.Rd: SingleCellExperiment-class getTopHVG.Rd: SingleCellExperiment-class importAlevin.Rd: DelayedArray, readMM importAnnData.Rd: DelayedArray, readMM importBUStools.Rd: readMM importCellRanger.Rd: readMM, DelayedArray importCellRangerV2Sample.Rd: readMM, DelayedArray importCellRangerV3Sample.Rd: readMM, DelayedArray importDropEst.Rd: DelayedArray, readMM importExampleData.Rd: scRNAseq, Matrix, DelayedArray, ReprocessedFluidigmData, ReprocessedAllenData, NestorowaHSCData importFromFiles.Rd: readMM, DelayedArray, SingleCellExperiment-class importGeneSetsFromCollection.Rd: GeneSetCollection-class, SingleCellExperiment-class, GeneSetCollection, GSEABase, metadata importGeneSetsFromGMT.Rd: GeneSetCollection-class, SingleCellExperiment-class, getGmt, GSEABase, metadata importGeneSetsFromList.Rd: GeneSetCollection-class, SingleCellExperiment-class, GSEABase, metadata importGeneSetsFromMSigDB.Rd: SingleCellExperiment-class, msigdbr, GeneSetCollection-class, GSEABase, metadata importMitoGeneSet.Rd: SingleCellExperiment-class, GeneSetCollection-class, GSEABase, metadata importMultipleSources.Rd: DelayedArray importOptimus.Rd: readMM, DelayedArray importSEQC.Rd: readMM, DelayedArray importSTARsolo.Rd: readMM, DelayedArray iterateSimulations.Rd: SingleCellExperiment-class listSampleSummaryStatsTables.Rd: SingleCellExperiment-class, metadata plotBarcodeRankDropsResults.Rd: SingleCellExperiment-class plotBarcodeRankScatter.Rd: SingleCellExperiment-class plotBatchCorrCompare.Rd: SingleCellExperiment-class plotBatchVariance.Rd: SingleCellExperiment-class plotBcdsResults.Rd: SingleCellExperiment-class plotClusterAbundance.Rd: colData plotCxdsResults.Rd: SingleCellExperiment-class plotDEGHeatmap.Rd: SingleCellExperiment-class plotDEGRegression.Rd: SingleCellExperiment-class plotDEGViolin.Rd: SingleCellExperiment-class plotDEGVolcano.Rd: SingleCellExperiment-class plotDecontXResults.Rd: SingleCellExperiment-class plotDoubletFinderResults.Rd: SingleCellExperiment-class plotEmptyDropsResults.Rd: SingleCellExperiment-class plotEmptyDropsScatter.Rd: SingleCellExperiment-class plotFindMarkerHeatmap.Rd: SingleCellExperiment-class plotPCA.Rd: SingleCellExperiment-class plotPathway.Rd: SingleCellExperiment-class plotRunPerCellQCResults.Rd: SingleCellExperiment-class plotSCEBarAssayData.Rd: SingleCellExperiment-class plotSCEBarColData.Rd: SingleCellExperiment-class plotSCEBatchFeatureMean.Rd: SingleCellExperiment-class plotSCEDensity.Rd: SingleCellExperiment-class plotSCEDensityAssayData.Rd: SingleCellExperiment-class plotSCEDensityColData.Rd: SingleCellExperiment-class plotSCEDimReduceColData.Rd: SingleCellExperiment-class plotSCEDimReduceFeatures.Rd: SingleCellExperiment-class plotSCEHeatmap.Rd: SingleCellExperiment-class plotSCEScatter.Rd: SingleCellExperiment-class plotSCEViolin.Rd: SingleCellExperiment-class plotSCEViolinAssayData.Rd: SingleCellExperiment-class plotSCEViolinColData.Rd: SingleCellExperiment-class plotScDblFinderResults.Rd: SingleCellExperiment-class plotScdsHybridResults.Rd: SingleCellExperiment-class plotScrubletResults.Rd: SingleCellExperiment-class plotSoupXResults.Rd: SingleCellExperiment-class plotTSCANClusterDEG.Rd: SingleCellExperiment-class plotTSCANClusterPseudo.Rd: SingleCellExperiment-class plotTSCANDimReduceFeatures.Rd: SingleCellExperiment-class plotTSCANPseudotimeGenes.Rd: SingleCellExperiment-class plotTSCANPseudotimeHeatmap.Rd: SingleCellExperiment-class plotTSCANResults.Rd: SingleCellExperiment-class plotTSNE.Rd: SingleCellExperiment-class plotUMAP.Rd: SingleCellExperiment-class readSingleCellMatrix.Rd: DelayedArray reportCellQC.Rd: SingleCellExperiment-class reportClusterAbundance.Rd: colData reportDiffAbundanceFET.Rd: colData retrieveSCEIndex.Rd: SingleCellExperiment-class runBBKNN.Rd: SingleCellExperiment-class runBarcodeRankDrops.Rd: SingleCellExperiment-class, colData runBcds.Rd: SingleCellExperiment-class, colData runCellQC.Rd: colData runComBatSeq.Rd: SingleCellExperiment-class runCxds.Rd: SingleCellExperiment-class, colData runCxdsBcdsHybrid.Rd: colData runDEAnalysis.Rd: SingleCellExperiment-class runDecontX.Rd: colData runDimReduce.Rd: SingleCellExperiment-class runDoubletFinder.Rd: SingleCellExperiment-class runDropletQC.Rd: colData runEmptyDrops.Rd: SingleCellExperiment-class, colData runEnrichR.Rd: SingleCellExperiment-class runFastMNN.Rd: SingleCellExperiment-class, BiocParallelParam-class runFeatureSelection.Rd: SingleCellExperiment-class runFindMarker.Rd: SingleCellExperiment-class runGSVA.Rd: SingleCellExperiment-class runHarmony.Rd: SingleCellExperiment-class runKMeans.Rd: SingleCellExperiment-class, colData runLimmaBC.Rd: SingleCellExperiment-class, assay runMNNCorrect.Rd: SingleCellExperiment-class, assay, BiocParallelParam-class runModelGeneVar.Rd: SingleCellExperiment-class runPerCellQC.Rd: SingleCellExperiment-class, BiocParallelParam, colData runSCANORAMA.Rd: SingleCellExperiment-class, assay runSCMerge.Rd: SingleCellExperiment-class, colData, assay, BiocParallelParam-class runScDblFinder.Rd: SingleCellExperiment-class, colData runScranSNN.Rd: SingleCellExperiment-class, reducedDim, assay, altExp, colData, igraph runScrublet.Rd: SingleCellExperiment-class, colData runSingleR.Rd: SingleCellExperiment-class runSoupX.Rd: SingleCellExperiment-class runTSCAN.Rd: SingleCellExperiment-class runTSCANClusterDEAnalysis.Rd: SingleCellExperiment-class runTSCANDEG.Rd: SingleCellExperiment-class runTSNE.Rd: SingleCellExperiment-class runUMAP.Rd: SingleCellExperiment-class, BiocParallelParam-class runVAM.Rd: SingleCellExperiment-class runZINBWaVE.Rd: SingleCellExperiment-class, colData, BiocParallelParam-class sampleSummaryStats.Rd: SingleCellExperiment-class, assay, colData scaterPCA.Rd: SingleCellExperiment-class, BiocParallelParam-class scaterlogNormCounts.Rd: logNormCounts sctkListGeneSetCollections.Rd: GeneSetCollection-class sctkPythonInstallConda.Rd: conda_install, reticulate, conda_create sctkPythonInstallVirtualEnv.Rd: virtualenv_install, reticulate, virtualenv_create selectSCTKConda.Rd: reticulate selectSCTKVirtualEnvironment.Rd: reticulate setRowNames.Rd: SingleCellExperiment-class setSCTKDisplayRow.Rd: SingleCellExperiment-class singleCellTK.Rd: SingleCellExperiment-class subsetSCECols.Rd: SingleCellExperiment-class subsetSCERows.Rd: SingleCellExperiment-class, altExp summarizeSCE.Rd: SingleCellExperiment-class Please provide package anchors for all Rd \link{} targets not in the package itself and the base packages. * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed runDoubletFinder 28.848 2.001 30.852 plotDoubletFinderResults 28.761 0.156 28.999 runSeuratSCTransform 28.285 0.589 28.877 plotScDblFinderResults 27.963 0.392 28.434 runScDblFinder 19.308 0.372 19.681 importExampleData 10.216 0.440 11.182 plotBatchCorrCompare 9.749 0.012 9.941 plotScdsHybridResults 7.542 0.037 6.894 plotBcdsResults 6.997 0.043 6.352 plotEmptyDropsResults 6.474 0.018 6.493 plotEmptyDropsScatter 6.410 0.011 6.420 runEmptyDrops 6.254 0.050 6.305 runDecontX 5.806 0.481 6.287 plotDecontXResults 6.110 0.102 6.212 plotUMAP 5.734 0.013 5.824 runUMAP 5.386 0.080 5.548 plotCxdsResults 5.355 0.071 5.506 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘spelling.R’ Running ‘testthat.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... OK * DONE Status: 2 NOTEs See ‘/home/biocbuild/bbs-3.21-bioc/meat/singleCellTK.Rcheck/00check.log’ for details.
singleCellTK.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL singleCellTK ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’ * installing *source* package ‘singleCellTK’ ... ** using staged installation ** R ** data ** exec ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (singleCellTK)
singleCellTK.Rcheck/tests/spelling.Rout
R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > if (requireNamespace('spelling', quietly = TRUE)) + spelling::spell_check_test(vignettes = TRUE, error = FALSE, skip_on_cran = TRUE) NULL > > proc.time() user system elapsed 0.129 0.036 0.151
singleCellTK.Rcheck/tests/testthat.Rout
R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(testthat) > library(singleCellTK) Loading required package: SummarizedExperiment Loading required package: MatrixGenerics Loading required package: matrixStats Attaching package: 'MatrixGenerics' The following objects are masked from 'package:matrixStats': colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse, colCounts, colCummaxs, colCummins, colCumprods, colCumsums, colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs, colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats, colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds, colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads, colWeightedMeans, colWeightedMedians, colWeightedSds, colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet, rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods, rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps, rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins, rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks, rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars, rowWeightedMads, rowWeightedMeans, rowWeightedMedians, rowWeightedSds, rowWeightedVars Loading required package: GenomicRanges Loading required package: stats4 Loading required package: BiocGenerics Loading required package: generics Attaching package: 'generics' The following objects are masked from 'package:base': as.difftime, as.factor, as.ordered, intersect, is.element, setdiff, setequal, union Attaching package: 'BiocGenerics' The following objects are masked from 'package:stats': IQR, mad, sd, var, xtabs The following objects are masked from 'package:base': Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append, as.data.frame, basename, cbind, colnames, dirname, do.call, duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind, rownames, sapply, saveRDS, table, tapply, unique, unsplit, which.max, which.min Loading required package: S4Vectors Attaching package: 'S4Vectors' The following object is masked from 'package:utils': findMatches The following objects are masked from 'package:base': I, expand.grid, unname Loading required package: IRanges Loading required package: GenomeInfoDb Loading required package: Biobase Welcome to Bioconductor Vignettes contain introductory material; view with 'browseVignettes()'. To cite Bioconductor, see 'citation("Biobase")', and for packages 'citation("pkgname")'. Attaching package: 'Biobase' The following object is masked from 'package:MatrixGenerics': rowMedians The following objects are masked from 'package:matrixStats': anyMissing, rowMedians Loading required package: SingleCellExperiment Loading required package: DelayedArray Loading required package: Matrix Attaching package: 'Matrix' The following object is masked from 'package:S4Vectors': expand Loading required package: S4Arrays Loading required package: abind Attaching package: 'S4Arrays' The following object is masked from 'package:abind': abind The following object is masked from 'package:base': rowsum Loading required package: SparseArray Attaching package: 'DelayedArray' The following objects are masked from 'package:base': apply, scale, sweep Attaching package: 'singleCellTK' The following object is masked from 'package:BiocGenerics': plotPCA > > test_check("singleCellTK") Found 2 batches Using null model in ComBat-seq. Adjusting for 0 covariate(s) or covariate level(s) Estimating dispersions Fitting the GLM model Shrinkage off - using GLM estimates for parameters Adjusting the data Found 2 batches Using null model in ComBat-seq. Adjusting for 1 covariate(s) or covariate level(s) Estimating dispersions Fitting the GLM model Shrinkage off - using GLM estimates for parameters Adjusting the data Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Uploading data to Enrichr... Done. Querying HDSigDB_Human_2021... Done. Parsing results... Done. Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating gene means 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating gene variance to mean ratios 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating gene means 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating gene variance to mean ratios 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck Number of nodes: 390 Number of edges: 9849 Running Louvain algorithm... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.8351 Number of communities: 7 Elapsed time: 0 seconds Using method 'umap' 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100% Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| [ FAIL 0 | WARN 20 | SKIP 0 | PASS 224 ] [ FAIL 0 | WARN 20 | SKIP 0 | PASS 224 ] > > proc.time() user system elapsed 222.984 6.562 231.450
singleCellTK.Rcheck/singleCellTK-Ex.timings
name | user | system | elapsed | |
MitoGenes | 0.001 | 0.001 | 0.002 | |
SEG | 0.003 | 0.000 | 0.003 | |
calcEffectSizes | 0.246 | 0.005 | 0.251 | |
combineSCE | 1.264 | 0.006 | 1.270 | |
computeZScore | 0.206 | 0.011 | 0.217 | |
convertSCEToSeurat | 3.570 | 0.102 | 3.672 | |
convertSeuratToSCE | 0.280 | 0.003 | 0.283 | |
dedupRowNames | 0.049 | 0.002 | 0.051 | |
detectCellOutlier | 4.443 | 0.037 | 4.480 | |
diffAbundanceFET | 0.050 | 0.002 | 0.052 | |
discreteColorPalette | 0.005 | 0.000 | 0.005 | |
distinctColors | 0.002 | 0.000 | 0.002 | |
downSampleCells | 0.455 | 0.034 | 0.489 | |
downSampleDepth | 0.364 | 0.001 | 0.365 | |
expData-ANY-character-method | 0.106 | 0.002 | 0.108 | |
expData-set-ANY-character-CharacterOrNullOrMissing-logical-method | 0.141 | 0.002 | 0.143 | |
expData-set | 0.133 | 0.001 | 0.133 | |
expData | 0.110 | 0.003 | 0.113 | |
expDataNames-ANY-method | 0.103 | 0.001 | 0.104 | |
expDataNames | 0.103 | 0.001 | 0.104 | |
expDeleteDataTag | 0.029 | 0.001 | 0.030 | |
expSetDataTag | 0.023 | 0.001 | 0.023 | |
expTaggedData | 0.023 | 0.001 | 0.023 | |
exportSCE | 0.021 | 0.000 | 0.021 | |
exportSCEtoAnnData | 0.084 | 0.011 | 0.094 | |
exportSCEtoFlatFile | 0.085 | 0.008 | 0.094 | |
featureIndex | 0.029 | 0.005 | 0.034 | |
generateSimulatedData | 0.062 | 0.000 | 0.062 | |
getBiomarker | 0.054 | 0.000 | 0.053 | |
getDEGTopTable | 0.575 | 0.007 | 0.582 | |
getDiffAbundanceResults | 0.044 | 0.001 | 0.045 | |
getEnrichRResult | 0.571 | 0.049 | 2.043 | |
getFindMarkerTopTable | 1.344 | 0.073 | 1.417 | |
getMSigDBTable | 0.004 | 0.000 | 0.004 | |
getPathwayResultNames | 0.018 | 0.004 | 0.021 | |
getSampleSummaryStatsTable | 0.165 | 0.000 | 0.165 | |
getSoupX | 0.000 | 0.000 | 0.001 | |
getTSCANResults | 0.946 | 0.011 | 0.957 | |
getTopHVG | 0.737 | 0.010 | 0.747 | |
importAnnData | 0.002 | 0.000 | 0.002 | |
importBUStools | 0.158 | 0.003 | 0.163 | |
importCellRanger | 0.629 | 0.005 | 0.635 | |
importCellRangerV2Sample | 0.122 | 0.000 | 0.123 | |
importCellRangerV3Sample | 0.257 | 0.001 | 0.259 | |
importDropEst | 0.172 | 0.000 | 0.174 | |
importExampleData | 10.216 | 0.440 | 11.182 | |
importGeneSetsFromCollection | 1.610 | 0.027 | 1.637 | |
importGeneSetsFromGMT | 0.057 | 0.002 | 0.059 | |
importGeneSetsFromList | 0.105 | 0.000 | 0.106 | |
importGeneSetsFromMSigDB | 3.203 | 0.131 | 3.334 | |
importMitoGeneSet | 0.045 | 0.002 | 0.047 | |
importOptimus | 0.002 | 0.000 | 0.001 | |
importSEQC | 0.125 | 0.010 | 0.136 | |
importSTARsolo | 0.139 | 0.018 | 0.157 | |
iterateSimulations | 0.154 | 0.032 | 0.187 | |
listSampleSummaryStatsTables | 0.235 | 0.026 | 0.261 | |
mergeSCEColData | 0.307 | 0.049 | 0.356 | |
mouseBrainSubsetSCE | 0.033 | 0.002 | 0.036 | |
msigdb_table | 0.001 | 0.001 | 0.002 | |
plotBarcodeRankDropsResults | 0.587 | 0.002 | 0.588 | |
plotBarcodeRankScatter | 0.576 | 0.003 | 0.579 | |
plotBatchCorrCompare | 9.749 | 0.012 | 9.941 | |
plotBatchVariance | 0.296 | 0.002 | 0.298 | |
plotBcdsResults | 6.997 | 0.043 | 6.352 | |
plotBubble | 0.623 | 0.007 | 0.630 | |
plotClusterAbundance | 0.731 | 0.002 | 0.732 | |
plotCxdsResults | 5.355 | 0.071 | 5.506 | |
plotDEGHeatmap | 1.934 | 0.005 | 1.940 | |
plotDEGRegression | 2.976 | 0.028 | 3.000 | |
plotDEGViolin | 3.635 | 0.010 | 3.639 | |
plotDEGVolcano | 0.738 | 0.003 | 0.741 | |
plotDecontXResults | 6.110 | 0.102 | 6.212 | |
plotDimRed | 0.217 | 0.001 | 0.218 | |
plotDoubletFinderResults | 28.761 | 0.156 | 28.999 | |
plotEmptyDropsResults | 6.474 | 0.018 | 6.493 | |
plotEmptyDropsScatter | 6.410 | 0.011 | 6.420 | |
plotFindMarkerHeatmap | 3.404 | 0.011 | 3.415 | |
plotMASTThresholdGenes | 1.194 | 0.009 | 1.202 | |
plotPCA | 0.278 | 0.002 | 0.280 | |
plotPathway | 0.486 | 0.006 | 0.492 | |
plotRunPerCellQCResults | 1.704 | 0.003 | 1.707 | |
plotSCEBarAssayData | 0.173 | 0.000 | 0.173 | |
plotSCEBarColData | 0.124 | 0.002 | 0.126 | |
plotSCEBatchFeatureMean | 0.191 | 0.010 | 0.201 | |
plotSCEDensity | 0.187 | 0.005 | 0.191 | |
plotSCEDensityAssayData | 0.176 | 0.008 | 0.184 | |
plotSCEDensityColData | 0.182 | 0.001 | 0.184 | |
plotSCEDimReduceColData | 0.433 | 0.004 | 0.438 | |
plotSCEDimReduceFeatures | 0.236 | 0.004 | 0.240 | |
plotSCEHeatmap | 0.364 | 0.002 | 0.366 | |
plotSCEScatter | 0.247 | 0.002 | 0.249 | |
plotSCEViolin | 0.213 | 0.002 | 0.215 | |
plotSCEViolinAssayData | 0.228 | 0.001 | 0.229 | |
plotSCEViolinColData | 0.214 | 0.002 | 0.216 | |
plotScDblFinderResults | 27.963 | 0.392 | 28.434 | |
plotScanpyDotPlot | 0.021 | 0.000 | 0.021 | |
plotScanpyEmbedding | 0.019 | 0.001 | 0.021 | |
plotScanpyHVG | 0.020 | 0.001 | 0.021 | |
plotScanpyHeatmap | 0.021 | 0.000 | 0.021 | |
plotScanpyMarkerGenes | 0.020 | 0.001 | 0.020 | |
plotScanpyMarkerGenesDotPlot | 0.020 | 0.001 | 0.021 | |
plotScanpyMarkerGenesHeatmap | 0.020 | 0.000 | 0.021 | |
plotScanpyMarkerGenesMatrixPlot | 0.020 | 0.001 | 0.021 | |
plotScanpyMarkerGenesViolin | 0.020 | 0.001 | 0.021 | |
plotScanpyMatrixPlot | 0.020 | 0.000 | 0.021 | |
plotScanpyPCA | 0.021 | 0.000 | 0.021 | |
plotScanpyPCAGeneRanking | 0.019 | 0.001 | 0.021 | |
plotScanpyPCAVariance | 0.020 | 0.001 | 0.021 | |
plotScanpyViolin | 0.021 | 0.000 | 0.021 | |
plotScdsHybridResults | 7.542 | 0.037 | 6.894 | |
plotScrubletResults | 0.022 | 0.000 | 0.021 | |
plotSeuratElbow | 0.020 | 0.001 | 0.021 | |
plotSeuratHVG | 0.020 | 0.001 | 0.021 | |
plotSeuratJackStraw | 0.021 | 0.000 | 0.021 | |
plotSeuratReduction | 0.021 | 0.000 | 0.021 | |
plotSoupXResults | 0 | 0 | 0 | |
plotTSCANClusterDEG | 3.237 | 0.007 | 3.246 | |
plotTSCANClusterPseudo | 1.084 | 0.002 | 1.086 | |
plotTSCANDimReduceFeatures | 1.087 | 0.003 | 1.089 | |
plotTSCANPseudotimeGenes | 1.235 | 0.002 | 1.238 | |
plotTSCANPseudotimeHeatmap | 1.218 | 0.006 | 1.225 | |
plotTSCANResults | 0.997 | 0.003 | 1.000 | |
plotTSNE | 0.321 | 0.001 | 0.322 | |
plotTopHVG | 0.483 | 0.004 | 0.486 | |
plotUMAP | 5.734 | 0.013 | 5.824 | |
readSingleCellMatrix | 0.004 | 0.000 | 0.004 | |
reportCellQC | 0.069 | 0.005 | 0.074 | |
reportDropletQC | 0.022 | 0.000 | 0.022 | |
reportQCTool | 0.075 | 0.000 | 0.075 | |
retrieveSCEIndex | 0.027 | 0.000 | 0.027 | |
runBBKNN | 0 | 0 | 0 | |
runBarcodeRankDrops | 0.212 | 0.001 | 0.213 | |
runBcds | 2.078 | 0.002 | 1.227 | |
runCellQC | 0.081 | 0.001 | 0.082 | |
runClusterSummaryMetrics | 0.365 | 0.004 | 0.369 | |
runComBatSeq | 0.471 | 0.005 | 0.476 | |
runCxds | 0.303 | 0.000 | 0.303 | |
runCxdsBcdsHybrid | 1.950 | 0.001 | 1.176 | |
runDEAnalysis | 0.356 | 0.002 | 0.358 | |
runDecontX | 5.806 | 0.481 | 6.287 | |
runDimReduce | 0.253 | 0.006 | 0.259 | |
runDoubletFinder | 28.848 | 2.001 | 30.852 | |
runDropletQC | 0.021 | 0.001 | 0.023 | |
runEmptyDrops | 6.254 | 0.050 | 6.305 | |
runEnrichR | 0.512 | 0.076 | 1.706 | |
runFastMNN | 1.563 | 0.172 | 1.736 | |
runFeatureSelection | 0.200 | 0.007 | 0.207 | |
runFindMarker | 1.278 | 0.019 | 1.296 | |
runGSVA | 0.673 | 0.027 | 0.701 | |
runHarmony | 0.033 | 0.002 | 0.035 | |
runKMeans | 0.159 | 0.002 | 0.160 | |
runLimmaBC | 0.07 | 0.00 | 0.07 | |
runMNNCorrect | 0.366 | 0.003 | 0.370 | |
runModelGeneVar | 0.277 | 0.001 | 0.278 | |
runNormalization | 2.032 | 0.262 | 2.294 | |
runPerCellQC | 0.291 | 0.002 | 0.294 | |
runSCANORAMA | 0 | 0 | 0 | |
runSCMerge | 0.003 | 0.001 | 0.004 | |
runScDblFinder | 19.308 | 0.372 | 19.681 | |
runScanpyFindClusters | 0.021 | 0.001 | 0.022 | |
runScanpyFindHVG | 0.021 | 0.000 | 0.021 | |
runScanpyFindMarkers | 0.021 | 0.000 | 0.021 | |
runScanpyNormalizeData | 0.090 | 0.005 | 0.095 | |
runScanpyPCA | 0.021 | 0.001 | 0.022 | |
runScanpyScaleData | 0.021 | 0.000 | 0.021 | |
runScanpyTSNE | 0.021 | 0.000 | 0.021 | |
runScanpyUMAP | 0.021 | 0.000 | 0.021 | |
runScranSNN | 0.266 | 0.033 | 0.300 | |
runScrublet | 0.021 | 0.001 | 0.022 | |
runSeuratFindClusters | 0.021 | 0.000 | 0.021 | |
runSeuratFindHVG | 0.439 | 0.044 | 0.483 | |
runSeuratHeatmap | 0.019 | 0.002 | 0.021 | |
runSeuratICA | 0.020 | 0.001 | 0.022 | |
runSeuratJackStraw | 0.021 | 0.000 | 0.022 | |
runSeuratNormalizeData | 0.020 | 0.001 | 0.021 | |
runSeuratPCA | 0.021 | 0.000 | 0.021 | |
runSeuratSCTransform | 28.285 | 0.589 | 28.877 | |
runSeuratScaleData | 0.022 | 0.000 | 0.022 | |
runSeuratUMAP | 0.019 | 0.001 | 0.020 | |
runSingleR | 0.032 | 0.000 | 0.032 | |
runSoupX | 0.001 | 0.000 | 0.000 | |
runTSCAN | 0.566 | 0.004 | 0.570 | |
runTSCANClusterDEAnalysis | 0.651 | 0.002 | 0.653 | |
runTSCANDEG | 1.896 | 0.004 | 1.900 | |
runTSNE | 0.683 | 0.002 | 0.685 | |
runUMAP | 5.386 | 0.080 | 5.548 | |
runVAM | 0.258 | 0.002 | 0.260 | |
runZINBWaVE | 0.003 | 0.001 | 0.003 | |
sampleSummaryStats | 0.134 | 0.002 | 0.136 | |
scaterCPM | 0.125 | 0.003 | 0.129 | |
scaterPCA | 0.381 | 0.002 | 0.384 | |
scaterlogNormCounts | 0.209 | 0.016 | 0.225 | |
sce | 0.019 | 0.001 | 0.020 | |
sctkListGeneSetCollections | 0.066 | 0.001 | 0.067 | |
sctkPythonInstallConda | 0 | 0 | 0 | |
sctkPythonInstallVirtualEnv | 0 | 0 | 0 | |
selectSCTKConda | 0.001 | 0.000 | 0.000 | |
selectSCTKVirtualEnvironment | 0 | 0 | 0 | |
setRowNames | 0.074 | 0.000 | 0.075 | |
setSCTKDisplayRow | 0.272 | 0.002 | 0.274 | |
singleCellTK | 0 | 0 | 0 | |
subDiffEx | 0.281 | 0.002 | 0.282 | |
subsetSCECols | 0.069 | 0.001 | 0.071 | |
subsetSCERows | 0.215 | 0.007 | 0.223 | |
summarizeSCE | 0.057 | 0.001 | 0.059 | |
trimCounts | 0.181 | 0.002 | 0.183 | |