To install this package, start R and enter:

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

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

GSAR

This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see GSAR.

Gene Set Analysis in R

Bioconductor version: 3.2

Gene set analysis using specific alternative hypotheses. Tests for differential expression, scale and net correlation structure.

Author: Yasir Rahmatallah <yrahmatallah at uams.edu>, Galina Glazko <gvglazko at uams.edu>

Maintainer: Yasir Rahmatallah <yrahmatallah at uams.edu>, Galina Glazko <gvglazko at uams.edu>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("GSAR")
PDF Gene Set Analysis in R -- the GSAR Package
PDF Reference Manual
Text NEWS

Details

biocViews DifferentialExpression, Software, StatisticalMethod
Version 1.4.0
In Bioconductor since BioC 3.0 (R-3.1) (1.5 years)
License GPL (>=2)
Depends R (>= 3.0.1), igraph (>= 0.7.0)
Imports
LinkingTo
Suggests MASS, GSVAdata, ALL, tweeDEseqCountData, GSEABase, annotate, org.Hs.eg.db, Biobase, genefilter, hgu95av2.db, edgeR, 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 GSAR_1.4.0.tar.gz
Windows Binary GSAR_1.4.0.zip
Mac OS X 10.6 (Snow Leopard) GSAR_1.4.0.tgz
Mac OS X 10.9 (Mavericks) GSAR_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/GSAR/tree/release-3.2
Package Short Url http://bioconductor.org/packages/GSAR/
Package Downloads Report Download Stats

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