a tool to identify genomic geatures with a specific biologically interesting pattern of associations with multiple endpoint variables
The PROMISE (PRojection Onto the Most Interesting Statistical Evidence) is performed by calling function PROMISE. The array data and endpoint data are passed through an ExpressionSet; the gene set definition is passed through a GeneSetCollection, and PROMISE definition is passed through a data frame. promise.genestat and avg.abs.genestat are called internally by PROMISE. Two R routines for calculating association statistics with individual endpoint variable(jung.rstat and spearman.rstat) are provided in this version. Users could provide their own R routines written in a similar fashion.
Jung, S-H, Owzar K, and Goerge SL (2005) A multiple testing procedure to associate gene expression levels with survival. Biostatistics 24: 3077-3088.
Goeman JJ and Buhlmann P (2007) Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 23: 980-987.
Pounds S, Cheng C, Cao X, Crews KR, Plunkett W, Gandhi V, Rubnitz J, Ribeiro RC, Downing JR, and Lamba J (2009) PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables. Bioinformatics 25: 2013-2019
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## load sampExprSet, sampGeneSet, phPatt. data(sampExprSet) data(sampGeneSet) data(phPatt) ## Perform PROMISE procedure without GSEA test1 <- PROMISE(exprSet=sampExprSet, geneSet=NULL, promise.pattern=phPatt, strat.var=NULL, proj0=FALSE, nbperm=FALSE, max.ntail=10, seed=13, nperms=100) ## Perform PROMISE procedure with GSEA and using fast permuation test2 <- PROMISE(exprSet=sampExprSet, geneSet=sampGeneSet, promise.pattern=phPatt, strat.var=NULL, proj0=TRUE, nbperm=TRUE, max.ntail=10, seed=13, nperms=100)
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