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This is the development version of GSAR; for the stable release version, see GSAR.

Gene Set Analysis in R

Bioconductor version: Development (3.19)

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 (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


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

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


biocViews DifferentialExpression, Software, StatisticalMethod
Version 1.37.0
In Bioconductor since BioC 3.0 (R-3.1) (9.5 years)
License GPL (>=2)
Depends R (>= 3.0.1), igraph (>= 0.7.1)
Imports stats, graphics
System Requirements
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Suggests MASS, GSVAdata, ALL, tweeDEseqCountData, GSEABase, annotate, org.Hs.eg.db, Biobase, genefilter, hgu95av2.db, edgeR, BiocStyle
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Package Archives

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

Source Package GSAR_1.37.0.tar.gz
Windows Binary GSAR_1.37.0.zip (64-bit only)
macOS Binary (x86_64) GSAR_1.37.0.tgz
macOS Binary (arm64) GSAR_1.37.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/GSAR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/GSAR
Bioc Package Browser https://code.bioconductor.org/browse/GSAR/
Package Short Url https://bioconductor.org/packages/GSAR/
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