To install this package, start R and enter:
source("http://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: 2.14
Differential expression analysis of RNA-seq and digital gene expression profiles with biological replication. Uses empirical Bayes estimation and exact tests based on the negative binomial distribution. Also useful for differential signal analysis with other types of genome-scale count data.
Author: Yunshun Chen <yuchen at wehi.edu.au>, Davis McCarthy <dmccarthy at wehi.edu.au>, Aaron Lun <alun at wehi.edu.au>, Mark Robinson <mark.robinson at imls.uzh.ch>, Xiaobei Zhou <xiaobei.zhou at uzh.ch>, Gordon Smyth <smyth at wehi.edu.au>
Maintainer: Yunshun Chen <yuchen 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:
source("http://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")
| R Script | edgeR Vignette | |
| edgeRUsersGuide.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 | 3.6.8 |
| In Bioconductor since | BioC 2.3 (R-2.8) |
| License | GPL (>=2) |
| Depends | R (>= 2.15.0), limma |
| Imports | methods |
| Suggests | MASS, statmod, splines, locfit, KernSmooth |
| System Requirements | |
| URL | http://bioinf.wehi.edu.au/edgeR |
| Depends On Me | DBChIP, EDDA, manta, methylMnM, MLSeq, TCC, tRanslatome |
| Imports Me | ampliQueso, ArrayExpressHTS, compcodeR, DiffBind, DSS, easyRNASeq, EDDA, HTSFilter, MEDIPS, metaseqR, msmsTests, Repitools, ReportingTools, rnaSeqMap, tweeDEseq |
| Suggests Me | baySeq, BitSeq, clonotypeR, cqn, EDASeq, gage, GenomicAlignments, GenomicRanges, goseq, GSVA, leeBamViews, oneChannelGUI, pasilla, SSPA |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | edgeR_3.6.8.tar.gz |
| Windows Binary | edgeR_3.6.8.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | edgeR_3.6.8.tgz |
| Mac OS X 10.9 (Mavericks) | edgeR_3.6.8.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
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