PRS: Pathway regulation score (PRS)

Description Usage Arguments Value Author(s) References See Also Examples

Description

This function implements the PRS method to analyze pathway enrichment of gene expression data. For PRS, a gene weight correspond to the number of downstream differentially expressed genes.

Usage

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prs(de, all, pwys, nperm = 1000)

prsWeights(pwy, de, all)

Arguments

de

A named numeric vector containing log2 fold-changes of the differentially expressed genes. Recommended names are Entrez gene IDs.

all

A character vector with the gene IDs in the reference set. If the data was obtained from a gene expression experiment, this set will contain all genes measured in the experiment. This vector should contain *all* names of the de argument.

pwys

A linkS4class{PathwayList} containing the pathways that should be analyzed for enrichment.

nperm

Integer. Number of permutations.

pwy

A linkS4class{Pathway} for which the weights should be computed.

Value

A data.frame with normalized score and p-value for each pathway analyzed.

Author(s)

Ivana Ihnatova

References

Ibrahim et al. (2012) A topology-based score for pathway enrichment. J Comput Biol, 19(5):563-73.

See Also

pathways

Examples

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# pathways
library(graphite)
pwys <- pathways("hsapiens","kegg")[1:10]

# expression data
all <- nodes(pwys[[1]])
nds <- sample(all, 30)
de <- setNames(rnorm(30), nds)

# executing PRS
prsWeights(pwys[[1]], de, all)
prs(de, all, pwys, nperm=100) 

ToPASeq documentation built on Nov. 8, 2020, 4:59 p.m.