To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("mvGST")

In most cases, you don't need to download the package archive at all.

mvGST

Multivariate and directional gene set testing

Bioconductor version: 3.1

mvGST provides platform-independent tools to identify GO terms (gene sets) that are differentially active (up or down) in multiple contrasts of interest. Given a matrix of one-sided p-values (rows for genes, columns for contrasts), mvGST uses meta-analytic methods to combine p-values for all genes annotated to each gene set, and then classify each gene set as being significantly more active (1), less active (-1), or not significantly differentially active (0) in each contrast of interest. With multiple contrasts of interest, each gene set is assigned to a profile (across contrasts) of differential activity. Tools are also provided for visualizing (in a GO graph) the gene sets classified to a given profile.

Author: John R. Stevens and Dennis S. Mecham

Maintainer: John R. Stevens <john.r.stevens at usu.edu>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("mvGST")

Documentation

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

browseVignettes("mvGST")

 

PDF R Script mvGST Tutorial Vignette
PDF   Reference Manual
Text   NEWS

Details

biocViews DifferentialExpression, GO, GeneSetEnrichment, GraphAndNetwork, Microarray, OneChannel, Pathways, RNASeq, Software
Version 1.2.0
In Bioconductor since BioC 3.0 (R-3.1) (1 year)
License GPL-3
Depends R (>= 2.10.0), GO.db, Rgraphviz
Imports gProfileR, stringr, topGO, GOstats, annotate, AnnotationDbi, graph
LinkingTo
Suggests hgu133plus2.db, org.Hs.eg.db
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source mvGST_1.2.0.tar.gz
Windows Binary mvGST_1.2.0.zip
Mac OS X 10.6 (Snow Leopard) mvGST_1.2.0.tgz
Mac OS X 10.9 (Mavericks) mvGST_1.2.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/mvGST/tree/release-3.1
Package Short Url http://bioconductor.org/packages/mvGST/
Package Downloads Report Download Stats

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