To install this package, start R and enter:

## try http if https is not available
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: 3.1

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 is not available
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	R Script	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	3.10.5
In Bioconductor since	BioC 2.3 (R-2.8) (7 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, ToPASeq, tweeDEseq
Suggests Me	baySeq, BitSeq, ClassifyR, clonotypeR, cqn, EDASeq, gage, GenomicAlignments, GenomicRanges, goseq, groHMM, GSAR, GSVA, leeBamViews, missMethyl, oneChannelGUI, pasilla, SSPA
Build Report

Package Archives

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

Package Source	edgeR_3.10.5.tar.gz
Windows Binary	edgeR_3.10.5.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard)	edgeR_3.10.5.tgz
Mac OS X 10.9 (Mavericks)	edgeR_3.10.5.tgz
Subversion source	(username/password: readonly)
Git source	https://github.com/Bioconductor-mirror/edgeR/tree/release-3.1
Package Short Url	http://bioconductor.org/packages/edgeR/
Package Downloads Report	Download Stats

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