GSALightning

DOI: 10.18129/B9.bioc.GSALightning    

Fast Permutation-based Gene Set Analysis

Bioconductor version: Release (3.11)

GSALightning provides a fast implementation of permutation-based gene set analysis for two-sample problem. This package is particularly useful when testing simultaneously a large number of gene sets, or when a large number of permutations is necessary for more accurate p-values estimation.

Author: Billy Heung Wing Chang

Maintainer: Billy Heung Wing Chang <billyheungwing at gmail.com>

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GSALightning")

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("GSALightning")

 

HTML	R Script	Vignette Title
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	BiologicalQuestion, DifferentialExpression, GeneExpression, GeneSetEnrichment, Software, Transcription
Version	1.16.0
In Bioconductor since	BioC 3.3 (R-3.3) (4.5 years)
License	GPL (>=2)
Depends	R (>= 3.3.0)
Imports	Matrix, data.table, stats
LinkingTo
Suggests	knitr, rmarkdown
SystemRequirements
Enhances
URL	https://github.com/billyhw/GSALightning
BugReports	https://github.com/billyhw/GSALightning/issues
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	GSALightning_1.16.0.tar.gz
Windows Binary	GSALightning_1.16.0.zip
macOS 10.13 (High Sierra)	GSALightning_1.16.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/GSALightning
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/GSALightning
Package Short Url	https://bioconductor.org/packages/GSALightning/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.11	Source Archive