getOR {netDx} | R Documentation

## Get relative proportion of patient classes that contribute to a set of networks

### Description

Get relative proportion of patient classes that contribute to a set of networks

### Usage

    getOR(pNetworks, pheno_DF, predClass, netFile, verbose = TRUE)

### Arguments

`pNetworks` | (matrix) rows are patients, columns are network file filenames. a[i,j] = 1 if patient i has a structural variant in network j; else a[i,j] = 0
`pheno_DF` | (data.frame) Column "ID" has unique patient identifiers; column "STATUS" has patient class
`predClass` | (char) Class for which predictor is being built
`netFile` | (char) vector of networks of interest (e.g. those passing feature selection)
`verbose` | (logical) print messages

### Details

Feature selected networks should have the property of being enriched in the class of interest; e.g. be enriched in 'case' relative to 'control'. When given a list of networks N, this method computes the number and proportion of patients that overlap N. A high relative fraction of the predicted class indicates successful feature selection. To create a ROC or precision-recall curve, several calls can be made to this function, one per cutoff.

### Value

List. 1) stats: statistics on group overlap with , This is a 2xK matrix, where rows are classes (predClass,other), and columns are: total samples, samples overlapping nets, 2) relEnr: relative enrichment of `predClass` over other

### Examples

    d <- tempdir()
    options(stringsAsFactors=FALSE)
    pids <- paste("P",seq_len(5),sep="")
    pheno <- data.frame(ID=pids,STATUS=c(rep("case",3),rep("control",2)))

    # write PSN
    m1 <- matrix(c("P1","P1","P2","P2","P3","P4",1,1,1),byrow=FALSE,ncol=3)
    write.table(m1,file=paste(d,"net1.txt",sep=getFileSep()),sep="\t",
    col.names=FALSE,row.names=FALSE,quote=FALSE)
    m2 <- matrix(c("P3","P4",1),nrow=1)
    write.table(m2,file=paste(d,"net2.txt",sep=getFileSep()),sep="\t",
    col.names=FALSE,row.names=FALSE,quote=FALSE)

    # compute enrichment
    x <- countPatientsInNet(d,dir(d,pattern=c("net1.txt","net2.txt")), pids)
    getOR(x,pheno,"case",colnames(x)) # should give large RelEnr

[Package netDx version 1.1.4 Index]