Bioconductor version: Release (3.16)
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 "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("GSAR")
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:
browseVignettes("GSAR")
R Script | Gene Set Analysis in R -- the GSAR Package | |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, Software, StatisticalMethod |
Version | 1.32.1 |
In Bioconductor since | BioC 3.0 (R-3.1) (8.5 years) |
License | GPL (>=2) |
Depends | R (>= 3.0.1), igraph (>= 0.7.1) |
Imports | stats, graphics |
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 | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | GSAR_1.32.1.tar.gz |
Windows Binary | GSAR_1.32.1.zip |
macOS Binary (x86_64) | GSAR_1.32.1.tgz |
macOS Binary (arm64) | GSAR_1.32.1.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/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.16 | Source Archive |
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