edgeR
Empirical Analysis of Digital Gene Expression Data in R
Bioconductor version: Release (3.20)
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 read counts, including ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE and CAGE.
Author: Yunshun Chen, Aaron TL Lun, Davis J McCarthy, Lizhong Chen, Pedro Baldoni, Matthew E Ritchie, Belinda Phipson, Yifang Hu, Xiaobei Zhou, Mark D Robinson, Gordon K Smyth
Maintainer: Yunshun Chen <yuchen at wehi.edu.au>, Gordon Smyth <smyth at wehi.edu.au>, Aaron Lun <infinite.monkeys.with.keyboards at gmail.com>, Mark Robinson <mark.robinson at imls.uzh.ch>
citation("edgeR")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("edgeR")
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("edgeR")
A brief introduction to edgeR | HTML | R Script |
edgeR User's Guide | ||
Reference Manual | ||
NEWS | Text |
Details
biocViews | AlternativeSplicing, BatchEffect, Bayesian, BiomedicalInformatics, CellBiology, ChIPSeq, Clustering, Coverage, DNAMethylation, DifferentialExpression, DifferentialMethylation, DifferentialSplicing, Epigenetics, FunctionalGenomics, GeneExpression, GeneSetEnrichment, Genetics, ImmunoOncology, MultipleComparison, Normalization, Pathways, QualityControl, RNASeq, Regression, SAGE, Sequencing, SingleCell, Software, SystemsBiology, TimeCourse, Transcription, Transcriptomics |
Version | 4.4.0 |
In Bioconductor since | BioC 2.3 (R-2.8) (16 years) |
License | GPL (>=2) |
Depends | R (>= 3.6.0), limma(>= 3.61.9) |
Imports | methods, graphics, stats, utils, locfit |
System Requirements | |
URL | https://bioinf.wehi.edu.au/edgeR/ https://bioconductor.org/packages/edgeR |
See More
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | edgeR_4.4.0.tar.gz |
Windows Binary (x86_64) | edgeR_4.4.0.zip |
macOS Binary (x86_64) | edgeR_4.4.0.tgz |
macOS Binary (arm64) | edgeR_4.3.21.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/edgeR |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/edgeR |
Bioc Package Browser | https://code.bioconductor.org/browse/edgeR/ |
Package Short Url | https://bioconductor.org/packages/edgeR/ |
Package Downloads Report | Download Stats |