To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("mvGST")
In most cases, you don't need to download the package archive at all.
This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see mvGST.
Bioconductor version: 3.4
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")):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("mvGST")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("mvGST")
Follow Installation instructions to use this package in your R session.
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