To install this package, start R and enter:

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

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

SeqGSEA

DOI: 10.18129/B9.bioc.SeqGSEA

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

Bioconductor version: Release (3.5)

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:

## try http:// if https:// URLs are not supported
source("https://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

Version 1.16.0
In Bioconductor since BioC 2.12 (R-3.0) (4.5 years)
License GPL (>= 3)
Imports methods, biomaRt
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Enhances
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Package Archives

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

Source Package SeqGSEA_1.16.0.tar.gz
Windows Binary SeqGSEA_1.16.0.zip
Mac OS X 10.11 (El Capitan) SeqGSEA_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/SeqGSEA
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