Takes a vector of statistics with each element corresponds to a gene or phosphorylation site, and calculates a combined statistics for those that belong to the same pathway or kinase.
PGs: an array of names indicating genes or substrates that belong to a given pathway or kinase.
T: a vector of statistics (z-scores converted) with each element correspond to a gene or phosphorylation site that belong to the same pathway or kinase.
minSize: the size of annotation groups to be considered for calculating enrichment. Groups that are smaller than the minSize will be removed from the analysis.
method: the p-value integration method for combining accross multiple treatments. Available methods are Stouffer, OSP, Fisher, and maxP. The default method is Stouffer.
Returns
a doublet corresponding to the enrichment after integration across all genes or substrates that belong to the same pathway or kinase, and the size of the mapped genes or substrates to that pathway or kinase.
Examples
# load the example datadata(PM)# load pathway annotationsdata(Pathways)# convert statistics into z-scoresPM.zscores <- apply(PM,2,function(x){qnorm(rank(x)/(nrow(PM)+1))})# Rotate the matrix by contrast 1, -1, -1 (i.e. up-regulation, down-regulation, dow-regulation).PM.rotated <- rotate3d(PM.zscores, contrast = c(1,-1,-1))# combine rotated statistics across treatmentsgene.pvalues <- apply(PM.rotated,1, geneStats)# compute statistics for all reactome pathwaysgene.zscores <- qnorm(gene.pvalues, lower.tail =FALSE)gst <- t(sapply(Pathways.reactome, pathwayStats, gene.zscores))