edgeR
Bioc currentEmpirical Analysis of Digital Gene Expression Data in R
Release Lineage
Entered 2.3 · Oct 22, 2008
Current · Requires R 4.6
Description
Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
357 0 exported
Complexity
6.7 avg / 70 max
Call network
357 nodes / 525 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
23,706
Files
260
Compiled share
24.2%
Has compiled src
Yes
Language breakdown
API
Exported functions
219
Internal functions
26
Testing & CI
Has tests
Yes
Test-to-code ratio
0.10
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
–
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
25%
Unsafe pattern score
2
Dep constraint coverage
16.7%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.6.0
System requirements
–
C++ standard
–
License
GPL (>=2)
License flags
not SPDX, not OSI
History
Versions
36
First release
2009-03-03
Latest release
2026-05-23
Avg cadence
178 days
Cold removal rate
100%
Dep drift
8
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Topics
Depended on by (287)
Bioconductor (254)
People
Yunshun Chen
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("edgeR")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.