Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: 2.9

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

Maintainer: Thomas J. Hardcastle <tjh48 at>

To install this package, start R and enter:


To cite this package in a publication, start R and enter:



PDF R Script baySeq
PDF   Reference Manual


biocViews Bioinformatics, HighThroughputSequencing, DifferentialExpression, MultipleComparisons, SAGE
Depends R (>= 2.3.0), methods
Suggests snow, edgeR
System Requirements
License GPL-3
Depends On Me segmentSeq
Imports Me segmentSeq
Suggests Me oneChannelGUI
Version 1.8.3
Since Bioconductor 2.5 (R-2.10)

Package Downloads

Package Source baySeq_1.8.3.tar.gz
Windows Binary (32- & 64-bit)
MacOS 10.5 (Leopard) binary baySeq_1.8.3.tgz
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Fred Hutchinson Cancer Research Center