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

baySeq

Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: 2.13

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>

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	1.16.0
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	Rcade, segmentSeq, TCC
Imports Me	segmentSeq
Suggests Me	oneChannelGUI

Package Archives

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

Package Source	baySeq_1.16.0.tar.gz
Windows Binary	baySeq_1.16.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard)	baySeq_1.16.0.tgz
Browse/checkout source	(username/password: readonly)
Package Downloads Report	Download Stats