PRS: Pathway regulation score (PRS)
In lgeistlinger/ToPASeq: Topology-based pathway analysis of RNA-seq data

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

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.

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

prsWeights(pwy, de, all)

`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.

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

Ivana Ihnatova

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

pathways

# 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)