Linnorm

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see Linnorm.

Linear model and normality based transformation method (Linnorm)


Bioconductor version: 3.7

Linnorm is an R package for the analysis of RNA-seq, scRNA-seq, ChIP-seq count data or any large scale count data. It transforms such datasets for parametric tests. In addition to the transformtion function (Linnorm), the following pipelines are implemented: 1. Library size/Batch effect normalization (Linnorm.Norm), 2. Cell subpopluation analysis and visualization using t-SNE or PCA K-means clustering or Hierarchical clustering (Linnorm.tSNE, Linnorm.PCA, Linnorm.HClust), 3. Differential expression analysis or differential peak detection using limma (Linnorm.limma), 4. Highly variable gene discovery and visualization (Linnorm.HVar), 5. Gene correlation network analysis and visualization (Linnorm.Cor), 6. Stable gene selection for scRNA-seq data; for users without or do not want to rely on spike-in genes (Linnorm.SGenes). 7. Data imputation. (under development) (Linnorm.DataImput). Linnorm can work with raw count, CPM, RPKM, FPKM and TPM. Additionally, the RnaXSim function is included for simulating RNA-seq data for the evaluation of DEG analysis methods.

Author: Shun Hang Yip <shunyip at bu.edu>, Panwen Wang <pwwang at pwwang.com>, Jean-Pierre Kocher <Kocher.JeanPierre at mayo.edu>, Pak Chung Sham <pcsham at hku.hk>, Junwen Wang <junwen at uw.edu>

Maintainer: Ken Shun Hang Yip <shunyip at bu.edu>

Citation (from within R, enter citation("Linnorm")):

Installation

To install this package, start R (version "3.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("Linnorm")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("Linnorm")
Linnorm User Manual PDF R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews BatchEffect, ChIPSeq, Clustering, DifferentialExpression, GeneExpression, Genetics, Network, Normalization, PeakDetection, RNASeq, Sequencing, SingleCell, Software, Transcription
Version 2.4.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License MIT + file LICENSE
Depends R (>= 3.4)
Imports Rcpp (>= 0.12.2), RcppArmadillo (>= 0.8.100.1.0), fpc, vegan, mclust, apcluster, ggplot2, ellipse, limma, utils, statmod, MASS, igraph, grDevices, graphics, fastcluster, ggdendro, zoo, stats, amap, Rtsne, gmodels
System Requirements
URL http://www.jjwanglab.org/Linnorm/
See More
Suggests BiocStyle, knitr, rmarkdown, gplots, RColorBrewer, moments, testthat
Linking To Rcpp, RcppArmadillo
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package Linnorm_2.4.0.tar.gz
Windows Binary Linnorm_2.4.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) Linnorm_2.4.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/Linnorm
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/Linnorm
Package Short Url https://bioconductor.org/packages/Linnorm/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.7 Source Archive