prs {ToPASeq} | R Documentation

## Pathway regulation score (PRS)

### 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

    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

    # 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)

[Package ToPASeq version 1.21.1 Index]