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.
Bioconductor version: Release (3.5)
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")
R Script | mvGST Tutorial Vignette | |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, GO, GeneSetEnrichment, GraphAndNetwork, Microarray, OneChannel, Pathways, RNASeq, Software |
Version | 1.10.0 |
In Bioconductor since | BioC 3.0 (R-3.1) (3 years) |
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 |
Follow Installation instructions to use this package in your R session.
Source Package | mvGST_1.10.0.tar.gz |
Windows Binary | mvGST_1.10.0.zip |
Mac OS X 10.11 (El Capitan) | mvGST_1.10.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/mvGST |
Package Short Url | http://bioconductor.org/packages/mvGST/ |
Package Downloads Report | Download Stats |
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