pairwisePhenoMannWhit: Mann-Whitney U test for shift in location of genes from gene...

In HTSanalyzeR: Gene set over-representation, enrichment and network analyses for high-throughput screens

Description

This function performs a Mann-Whitney U test for shift in location of genes from gene sets, on a pair of phenotypes. It looks for gene sets that are represented towards the two different ends of two ranked lists of genes, i.e. whose phenotype distribution is located around two different ends of the two phenotype vectors, rather than spread on the whole list in both lists.

Usage

pairwisePhenoMannWhit(gl1, gl2, gsc, minGeneSetSize=15, pAdjustMethod="BH")

Arguments

gl1	a named numeric or integer vector where names are gene identifiers of the same type as the ones in the gene set collection, and values are the measurements on phenotype one corresponding to those genes. This vector MUST be ordered (decreasing or increasing)
gl2	a named numeric or integer vector where names are gene identifiers of the same type as the ones in the gene set collection, and values are the measurements on phenotype two corresponding to those genes. This vector MUST be ordered
gsc	a list of gene sets, each of which in the list is a character vector of gene identifiers.
minGeneSetSize	a single numeric or integer value specifying the minimum size required for a gene set to be considered.
pAdjustMethod	a single character value specifying the p-value adjustment method to be used (see 'p.adjust' for details)

Value

a table with a row for each gene set, containing the p-value for the Mann-Whitney U test, and the adjusted p-value. The table is ordered by the p-value column.

Author(s)

Camille Terfve, Xin Wang

See Also

pairwiseGseaPlot, pairwiseGsea

Examples

gl1 <- runif(100, min=-5, max=5)
gl2 <- runif(100, min=-5, max=5)
names(gl1) <- as.character(sample(x=seq(from=1, to=100, by=1), size=100,
replace=FALSE))
names(gl2) <- names(gl1)
gs1 <- sample(names(gl1), size=20, replace=FALSE)
gs2 <- sample(names(gl1), size=20, replace=FALSE)
gsc <- list(subset1=gs1, subset2=gs2)
pwGSC <- pairwisePhenoMannWhit(gl1=gl1, gl2=gl2, gsc=gsc, minGeneSetSize=2)

HTSanalyzeR documentation built on Oct. 31, 2019, 7:10 a.m.