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 (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 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 Advanced baySeq analyses
PDF R Script baySeq
PDF   Reference Manual

Details

biocViews DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software
Version 2.0.50
In Bioconductor since BioC 2.5 (R-2.10)
License GPL-3
Depends R (>= 2.3.0), methods, GenomicRanges, abind
Imports
Suggests snow, edgeR, BiocStyle, BiocGenerics
System Requirements
URL
Depends On Me EDDA, Rcade, segmentSeq, TCC
Imports Me EDDA, metaseqR
Suggests Me compcodeR, oneChannelGUI, riboSeqR

Package Archives

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

Package Source baySeq_2.0.50.tar.gz
Windows Binary baySeq_2.0.50.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) baySeq_2.0.50.tgz
Mac OS X 10.9 (Mavericks) baySeq_2.0.50.tgz
Browse/checkout source (username/password: readonly)
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