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Last data update: 2014.03.03

R: Function to use PRS method on microarray or RNA-Seq data

PRS	R Documentation

Function to use PRS method on microarray or RNA-Seq data

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(x, group, pathways, type, 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 data, `"MA"` for microarray, `"RNASeq"` for RNA-Seq, `DEtable` data.frame from differential expression analysis, or `DEGlist` a list of: log fold-changes of differentially expressed genes and names of the all genes analyses
`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 TMM-normalization is performed. Possible values are: `"TMM", "DESeq2", "rLog", "none"`. Ignored for type: "MA","DEtable", "DElist"
`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"`. Ignored for type: "MA","DEtable", "DElist"
`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(DEGraph)) {
  data("Loi2008_DEGraphVignette")
  pathways<-pathways("hsapiens","biocarta")[1:10]
  PRS( exprLoi2008, classLoi2008, pathways, type="MA",  logFC.th=-1, nperm=100)
}
## Not run: 
if (require(gageData)) {

 data(hnrnp.cnts)
 hnrnp.cnts<-hnrnp.cnts[rowSums(hnrnp.cnts)>0,]
 group<-c(rep("sample",4), rep("control",4))
 pathways<-pathways("hsapiens","biocarta")[1:10]
 PRS(hnrnp.cnts, group, pathways, type="RNASeq", logFC.th=-1, nperm=100, test="vstlimma")
}

## End(Not run)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'license()' or 'licence()' for distribution details.

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(ToPASeq)
Loading required package: graphite
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: gRbase
Loading required package: graph
Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: Rgraphviz
Loading required package: grid
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/ToPASeq/PRS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PRS
> ### Title: Function to use PRS method on microarray or RNA-Seq data
> ### Aliases: PRS
> ### Keywords: htest
> 
> ### ** Examples
> 
> 
> if (require(DEGraph)) {
+   data("Loi2008_DEGraphVignette")
+   pathways<-pathways("hsapiens","biocarta")[1:10]
+   PRS( exprLoi2008, classLoi2008, pathways, type="MA",  logFC.th=-1, nperm=100)
+ }
Loading required package: DEGraph
Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called 'DEGraph'
> ## Not run: 
> ##D if (require(gageData)) {
> ##D 
> ##D  data(hnrnp.cnts)
> ##D  hnrnp.cnts<-hnrnp.cnts[rowSums(hnrnp.cnts)>0,]
> ##D  group<-c(rep("sample",4), rep("control",4))
> ##D  pathways<-pathways("hsapiens","biocarta")[1:10]
> ##D  PRS(hnrnp.cnts, group, pathways, type="RNASeq", logFC.th=-1, nperm=100, test="vstlimma")
> ##D }
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>