GSAR
Gene Set Analysis in R
Bioconductor version: Release (3.17)
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("GSAR")
):
Installation
To install this package, start R (version "4.3") 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.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GSAR")
Gene Set Analysis in R -- the GSAR Package | R Script | |
Reference Manual | ||
NEWS | Text |
Details
biocViews | DifferentialExpression, Software, StatisticalMethod |
Version | 1.34.0 |
In Bioconductor since | BioC 3.0 (R-3.1) (9 years) |
License | GPL (>=2) |
Depends | R (>= 3.0.1), igraph (>= 0.7.1) |
Imports | stats, graphics |
Linking To | |
Suggests | MASS, GSVAdata, ALL, tweeDEseqCountData, GSEABase, annotate, org.Hs.eg.db, Biobase, genefilter, hgu95av2.db, edgeR, BiocStyle |
System Requirements | |
Enhances | |
URL |
See More
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | GSAR_1.34.0.tar.gz |
Windows Binary | GSAR_1.34.0.zip |
macOS Binary (x86_64) | GSAR_1.34.0.tgz |
macOS Binary (arm64) | GSAR_1.34.0.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/ |
Package Downloads Report | Download Stats |