To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("GSAR")

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

GSAR

Gene Set Analysis in R

Bioconductor version: Release (3.1)

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")):

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("GSAR")

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

browseVignettes("GSAR")

PDF	R Script	Gene Set Analysis in R -- the GSAR Package
PDF		Reference Manual
Text		NEWS

biocViews	DifferentialExpression, Software, StatisticalMethod
Version	1.2.2
In Bioconductor since	BioC 3.0 (R-3.1) (1 year)
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

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

Package Source	GSAR_1.2.2.tar.gz
Windows Binary	GSAR_1.2.2.zip
Mac OS X 10.6 (Snow Leopard)	GSAR_1.2.2.tgz
Mac OS X 10.9 (Mavericks)	GSAR_1.2.2.tgz
Subversion source	(username/password: readonly)
Git source	https://github.com/Bioconductor-mirror/GSAR/tree/release-3.1
Package Short Url	http://bioconductor.org/packages/GSAR/
Package Downloads Report	Download Stats

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