To install this package, start R and enter:

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

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

SeqGSEA

Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing

Bioconductor version: Release (2.14)

The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.

Author: Xi Wang <Xi.Wang at newcastle.edu.au>

Maintainer: Xi Wang <Xi.Wang at mdc-berlin.de>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("SeqGSEA")

 

PDF R Script Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package
PDF   Reference Manual
Text   NEWS

Details

biocViews DifferentialExpression, GeneExpression, GeneSetEnrichment, RNASeq, Sequencing, Software
Version 1.4.0
In Bioconductor since BioC 2.12 (R-3.0)
License GPL (>= 3)
Depends Biobase, doParallel, DESeq
Imports methods, biomaRt
Suggests easyRNASeq, GenomicRanges
System Requirements
URL
Depends On Me
Imports Me
Suggests Me

Package Archives

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

Package Source SeqGSEA_1.4.0.tar.gz
Windows Binary SeqGSEA_1.4.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) SeqGSEA_1.4.0.tgz
Mac OS X 10.9 (Mavericks) SeqGSEA_1.4.0.tgz
Browse/checkout source (username/password: readonly)
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