PRS_wrapper: Pathway Regulation Score (PRS)
In ToPASeq: Topology-based pathway analysis of RNA-seq data

Description Usage Arguments Value Author(s) References Examples

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.

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)

`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()`

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

Ivana Ihnatova

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

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)
}