GISPA

DOI: 10.18129/B9.bioc.GISPA    

This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see GISPA.

GISPA: Method for Gene Integrated Set Profile Analysis

Bioconductor version: 3.11

GISPA is a method intended for the researchers who are interested in defining gene sets with similar, a priori specified molecular profile. GISPA method has been previously published in Nucleic Acid Research (Kowalski et al., 2016; PMID: 26826710).

Author: Bhakti Dwivedi and Jeanne Kowalski

Maintainer: Bhakti Dwivedi <bhakti.dwivedi at emory.edu>

Citation (from within R, enter citation("GISPA")):

Installation

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

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

BiocManager::install("GISPA")

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("GISPA")

 

HTML R Script GISPA:Method for Gene Integrated Set Profile Analysis
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneSetEnrichment, GenomeWideAssociation, Software, StatisticalMethod
Version 1.12.0
In Bioconductor since BioC 3.5 (R-3.4) (3.5 years)
License GPL-2
Depends R (>= 3.3.2)
Imports Biobase, changepoint, data.table, genefilter, graphics, GSEABase, HH, lattice, latticeExtra, plyr, scatterplot3d, stats
LinkingTo
Suggests knitr
SystemRequirements
Enhances
URL
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 GISPA_1.12.0.tar.gz
Windows Binary GISPA_1.12.0.zip
macOS 10.13 (High Sierra) GISPA_1.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/GISPA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/GISPA
Package Short Url https://bioconductor.org/packages/GISPA/
Package Downloads Report Download Stats

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