To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("edgeR")

In most cases, you don't need to download the package archive at all.

edgeR

   

Empirical analysis of digital gene expression data in R

Bioconductor version: 3.2

Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, SAGE and CAGE.

Author: Yunshun Chen <yuchen at wehi.edu.au>, Aaron Lun <alun at wehi.edu.au>, Davis McCarthy <dmccarthy at wehi.edu.au>, Xiaobei Zhou <xiaobei.zhou at uzh.ch>, Mark Robinson <mark.robinson at imls.uzh.ch>, Gordon Smyth <smyth at wehi.edu.au>

Maintainer: Yunshun Chen <yuchen at wehi.edu.au>, Aaron Lun <alun at wehi.edu.au>, Mark Robinson <mark.robinson at imls.uzh.ch>, Davis McCarthy <dmccarthy at wehi.edu.au>, Gordon Smyth <smyth at wehi.edu.au>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("edgeR")

Documentation

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

browseVignettes("edgeR")

 

PDF edgeR Vignette
PDF edgeRUsersGuide.pdf
PDF   Reference Manual
Text   NEWS

Details

biocViews AlternativeSplicing, BatchEffect, Bayesian, ChIPSeq, Clustering, Coverage, DifferentialExpression, DifferentialSplicing, GeneExpression, GeneSetEnrichment, Genetics, MultipleComparison, Normalization, QualityControl, RNASeq, Regression, SAGE, Sequencing, Software, TimeCourse, Transcription
Version 3.12.1
In Bioconductor since BioC 2.3 (R-2.8) (7.5 years)
License GPL (>=2)
Depends R (>= 2.15.0), limma
Imports methods
LinkingTo
Suggests MASS, statmod, splines, locfit, KernSmooth
SystemRequirements
Enhances
URL http://bioinf.wehi.edu.au/edgeR
Depends On Me DBChIP, EDDA, manta, methylMnM, MLSeq, RnaSeqSampleSizeData, RUVSeq, TCC, tRanslatome
Imports Me ampliQueso, ArrayExpressHTS, compcodeR, csaw, DEGreport, DiffBind, diffHic, easyRNASeq, EDDA, EnrichmentBrowser, erccdashboard, HTSFilter, MEDIPS, metaseqR, msmsTests, PROPER, Repitools, ReportingTools, rnaSeqMap, RnaSeqSampleSize, STATegRa, systemPipeR, TCGAbiolinks, ToPASeq, tweeDEseq
Suggests Me baySeq, biobroom, BitSeq, ClassifyR, clonotypeR, cqn, EDASeq, gage, GenomicAlignments, GenomicRanges, goseq, groHMM, GSAR, GSVA, leeBamViews, missMethyl, oneChannelGUI, pasilla, SSPA, subSeq, variancePartition
Build Report  

Package Archives

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

Package Source edgeR_3.12.1.tar.gz
Windows Binary edgeR_3.12.1.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) edgeR_3.12.0.tgz
Mac OS X 10.9 (Mavericks) edgeR_3.12.1.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/edgeR/tree/release-3.2
Package Short Url http://bioconductor.org/packages/edgeR/
Package Downloads Report Download Stats

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