To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("baySeq")

In most cases, you don't need to download the package archive at all.

baySeq

Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: Release (2.14)

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 cam.ac.uk>

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

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("baySeq")

Documentation

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

browseVignettes("baySeq")

 

PDF R Script baySeq
PDF   Reference Manual

Details

biocViews Bioinformatics, DifferentialExpression, HighThroughputSequencing, MultipleComparisons, SAGE, Software
Version 1.18.0
In Bioconductor since BioC 2.5 (R-2.10)
License GPL-3
Depends R (>= 2.3.0), methods, GenomicRanges
Imports
Suggests snow, edgeR
System Requirements
URL
Depends On Me EDDA, Rcade, segmentSeq, TCC
Imports Me EDDA, metaseqR, segmentSeq
Suggests Me compcodeR, oneChannelGUI

Package Archives

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

Package Source baySeq_1.18.0.tar.gz
Windows Binary baySeq_1.18.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) baySeq_1.18.0.tgz
Mac OS X 10.9 (Mavericks) baySeq_1.18.0.tgz
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