edgeR

DOI: 10.18129/B9.bioc.edgeR    

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

Empirical Analysis of Digital Gene Expression Data in R

Bioconductor version: 3.7

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, Bisulfite-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, DNAMethylation, DifferentialExpression, DifferentialMethylation, DifferentialSplicing, GeneExpression, GeneSetEnrichment, Genetics, MultipleComparison, Normalization, Pathways, QualityControl, RNASeq, Regression, SAGE, Sequencing, Software, TimeCourse, Transcription
Version 3.22.5
In Bioconductor since BioC 2.3 (R-2.8) (10 years)
License GPL (>=2)
Depends R (>= 2.15.0), limma(>= 3.34.5)
Imports graphics, stats, utils, methods, locfit, Rcpp
LinkingTo Rcpp
Suggests AnnotationDbi, org.Hs.eg.db, readr, splines
SystemRequirements C++11
Enhances
URL http://bioinf.wehi.edu.au/edgeR
Depends On Me ASpli, chipseqDB, DBChIP, EDDA, EGSEA123, IntEREst, manta, methylMnM, RNAseq123, RnaSeqGeneEdgeRQL, RnaSeqSampleSizeData, RUVSeq, samExploreR, simpleSingleCell, TCC, tRanslatome
Imports Me affycoretools, ampliQueso, anota2seq, ArrayExpressHTS, baySeq, compcodeR, coseq, csaw, debrowser, DEComplexDisease, DEFormats, DEGreport, DEsubs, DiffBind, diffcyt, diffHic, diffloop, DRIMSeq, DropletUtils, easyRNASeq, EBSEA, EDDA, eegc, EGSEA, EnrichmentBrowser, erccdashboard, GDCRNATools, Glimma, GSEABenchmarkeR, HTSFilter, IsoformSwitchAnalyzeR, MEDIPS, metaseqR, MIGSA, MLSeq, msgbsR, msmsTests, PathoStat, PROPER, psichomics, recountWorkflow, regsplice, Repitools, ReportingTools, rnaSeqMap, RnaSeqSampleSize, scater, scde, scone, scran, singscore, splatter, STATegRa, SVAPLSseq, systemPipeR, TCGAbiolinks, TCseq, tweeDEseq, vidger, yarn, zinbwave
Suggests Me ABSSeq, biobroom, BitSeq, ClassifyR, clonotypeR, cqn, cydar, DEScan2, EDASeq, gage, gCrisprTools, GenomicAlignments, GenomicRanges, goseq, groHMM, GSAR, GSVA, ideal, JctSeqData, leeBamViews, missMethyl, multiMiR, regionReport, SSPA, stageR, subSeq, SummarizedBenchmark, tximport, variancePartition, zFPKM
Links To Me
Build Report  

Package Archives

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

Source Package edgeR_3.22.5.tar.gz
Windows Binary edgeR_3.22.5.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) edgeR_3.22.5.tgz
Source Repository git clone https://git.bioconductor.org/packages/edgeR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/edgeR
Package Short Url http://bioconductor.org/packages/edgeR/
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