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|
|Bioconductor views||DifferentialExpression GO GeneSetEnrichment GraphAndNetwork Microarray OneChannel Pathways RNASeq|
|Maintainer||John R. Stevens <[email protected]>|
|Package repository||View on GitHub|
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