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Multivariate and directional gene set testing

Bioconductor version: 3.0

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>

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PDF R Script mvGST Tutorial Vignette
PDF   Reference Manual
Text   NEWS


biocViews DifferentialExpression, GO, GeneSetEnrichment, GraphAndNetwork, Microarray, OneChannel, Pathways, RNASeq, Software
Version 1.0.0
In Bioconductor since BioC 3.0 (R-3.1)
License GPL-3
Depends R (>= 2.10.0), GO.db, Rgraphviz
Imports gProfileR, stringr, topGO, GOstats, annotate, AnnotationDbi, graph
Suggests hgu133plus2.db,
Depends On Me
Imports Me
Suggests Me
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