To install this package, start R and enter:

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

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

BitSeq

 

Transcript expression inference and differential expression analysis for RNA-seq data

Bioconductor version: Release (3.1)

The BitSeq package is targeted for transcript expression analysis and differential expression analysis of RNA-seq data in two stage process. In the first stage it uses Bayesian inference methodology to infer expression of individual transcripts from individual RNA-seq experiments. The second stage of BitSeq embraces the differential expression analysis of transcript expression. Providing expression estimates from replicates of multiple conditions, Log-Normal model of the estimates is used for inferring the condition mean transcript expression and ranking the transcripts based on the likelihood of differential expression.

Author: Peter Glaus, Antti Honkela and Magnus Rattray

Maintainer: Antti Honkela <antti.honkela at hiit.fi>, Panagiotis Papastamoulis <panagiotis.papastamoulis at manchester.ac.uk>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("BitSeq")

 

PDF R Script BitSeq User Guide
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews AlternativeSplicing, Bayesian, DifferentialExpression, DifferentialSplicing, GeneExpression, RNASeq, Sequencing, Software, Transcription
Version 1.12.0
In Bioconductor since BioC 2.10 (R-2.15) (3.5 years)
License Artistic-2.0 + file LICENSE
Depends Rsamtools, zlibbioc
Imports S4Vectors, IRanges
LinkingTo Rsamtools(>= 1.19.38), zlibbioc
Suggests edgeR, DESeq, BiocStyle
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source BitSeq_1.12.0.tar.gz
Windows Binary BitSeq_1.12.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) BitSeq_1.12.0.tgz
Mac OS X 10.9 (Mavericks) BitSeq_1.12.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/BitSeq/tree/release-3.1
Package Short Url http://bioconductor.org/packages/BitSeq/
Package Downloads Report Download Stats

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