Registration Open for Bioc2024 July 24-26


Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: Release (3.19)

This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

Author: Thomas J. Hardcastle [aut], Samuel Granjeaud [cre]

Maintainer: Samuel Granjeaud <samuel.granjeaud at>

Citation (from within R, enter citation("baySeq")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Advanced baySeq analyses PDF R Script
baySeq PDF R Script
Reference Manual PDF


biocViews Bayesian, Coverage, DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software
Version 2.38.0
In Bioconductor since BioC 2.5 (R-2.10) (14.5 years)
License GPL-3
Depends R (>= 2.3.0), methods
Imports edgeR, GenomicRanges, abind, parallel, graphics, stats, utils
System Requirements
Bug Reports
See More
Suggests BiocStyle, BiocGenerics
Linking To
Depends On Me clusterSeq, segmentSeq
Imports Me riboSeqR
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package baySeq_2.38.0.tar.gz
Windows Binary
macOS Binary (x86_64) baySeq_2.38.0.tgz
macOS Binary (arm64) baySeq_2.38.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats