Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: Development (3.0)

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, DifferentialExpression, HighThroughputSequencing, MultipleComparisons, SAGE, Software
Version 1.19.0
In Bioconductor since BioC 2.5 (R-2.10)
License GPL-3
Depends R (>= 2.3.0), methods, GenomicRanges
Suggests snow, edgeR
System Requirements
Depends On Me EDDA, Rcade, segmentSeq, TCC
Imports Me EDDA, metaseqR, segmentSeq
Suggests Me compcodeR, oneChannelGUI

Package Downloads

Package Source baySeq_1.19.0.tar.gz
Windows Binary (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) baySeq_1.19.0.tgz
Mac OS X 10.9 (Mavericks)
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