PRS_wrapper {ToPASeq} | R Documentation

## Pathway Regulation Score (PRS)

### Description

A function runs PRS method on a gene expression data matrix or count matrix and vector dividing samples into two groups and a set of pathways from `graphite` package. The PRS method (please see Reference for the details) was adapted to `graphite`'s graphs where each node is represented only by one gene.

### Usage

    PRS_wrapper(x, group, pathways, type, which = "proteins",
      edgeType = NULL, preparePaths = TRUE, norm.method = NULL,
      test.method = NULL, p.th = 0.05, logFC.th = 2, nperm = 1000,
      both.directions = TRUE, maxNodes = 150, minEdges = 0,
      commonTh = 2, filterSPIA = FALSE, convertTo = "none",
      convertBy = NULL)

### Arguments

`x` | An `ExpressionSet` object or a gene expression data matrix or count matrix, rows refer to genes, columns to samples
`group` | Name or number of the phenoData column or a character vector or factor that contains required class assigments
`pathways` | A list of pathways in a form from `graphite` package or created by `preparePathways()`
`type` | Type of the input data, `"MA"` for microarray and `"RNASeq"` for RNA-Seq
`which` | Character, which type of nodes is preserved in a pathway. Possible values are `"proteins"`,`"metabolites"`,`"mixed"`
`edgeType` | Character, which type of edges is preserved in a pathway. If `NULL`, all edges are kept.
`preparePaths` | Logical, by default the pathways are transformed with `preparePathways()`. Use `FALSE`, if you have done this transformation separately
`norm.method` | Character, the method to normalize RNAseq data. If `NULL` then vst-normalization is performed. Possible values are: `"edgeR", "vst", "rLog", "none"`
`test.method` | Character, the method for differentiall expression analysis of RNAseq data. If `NULL` then `"voomlimma"` is used. Possible values are: `"DESeq2", "voomlimma", "vstlimma", "edgeR"`. This analysis is needed only for the visualization.
`p.th` | Numeric, threshold for p-values of tests for differential expression of genes. Use `1` if you don't want any threshold to be applied
`logFC.th` | Numeric, threshold for log fold-change of a gene to identify the gene as differentially expressed. Use negative if you don't want any threshold to be applied
`nperm` | Numeric, number of permutations
`both.directions, maxNodes, minEdges, commonTh, filterSPIA, convertTo, convertBy` | Arguments for the `preparePathways()`

### Value

A list:

`res` | A data frame with normalized score, p-value and FDR-adjusted p-value for each pathway
`topo.sig` | A list with log fold-changes and number of downstream differentially expressed nodes for nodes of individual pathways
`degtest` | A named vector of statistics from testing the differential expression of genes

### Author(s)

Ivana Ihnatova

### References

Maysson Al-Haj Ibrahim, Sabah Jassim, Michael Anthony Cawthorne, and Kenneth Langlands. A Topology-Based Score for Pathway Enrichment, Journal of Computational Biology. May 2012, 19(5): 563-573

### Examples

    if (require(breastCancerVDX)) {
    data("vdx")
    pathways<-pathways("hsapiens","biocarta")[1:3]
    MAdata<-Biobase::exprs(vdx)[,1:10]
    rownames(MAdata)<-Biobase::fData(vdx)[,"Gene.symbol"]
    MAdata<-MAdata[!duplicated(rownames(MAdata)),]

    PRS_wrapper(MAdata, Biobase::pData(vdx)[,"er"][1:10], pathways, type="MA", convertTo="SYMBOL", logFC.th=-1, nperm=100)
    }

[Package ToPASeq version 1.20.0 Index]