To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("baySeq")

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

baySeq

   

This package is for version 2.10 of Bioconductor; for the stable, up-to-date release version, see baySeq.

Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: 2.10

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:

## try http:// if https:// URLs are not supported
source("https://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 baySeq
PDF   Reference Manual

Details

biocViews Bioinformatics, DifferentialExpression, HighThroughputSequencing, MultipleComparisons, SAGE, Software
Version 1.10.0
In Bioconductor since BioC 2.5 (R-2.10) (6.5 years)
License GPL-3
Depends R (>= 2.3.0), methods
Imports
LinkingTo
Suggests snow, edgeR
SystemRequirements
Enhances
URL
Depends On Me segmentSeq
Imports Me segmentSeq
Suggests Me oneChannelGUI
Build Report  

Package Archives

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

Package Source baySeq_1.10.0.tar.gz
Windows Binary baySeq_1.10.0.zip
Mac OS X 10.6 (Snow Leopard)
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/baySeq/tree/release-2.10
Package Short Url http://bioconductor.org/packages/baySeq/
Package Downloads Report Download Stats

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