getPatientRankings: Process GM PRANK files to get the ROC curve for the query

In BaderLab/netDx: Network-based patient classifier

Description

Process GM PRANK files to get the ROC curve for the query

Usage

getPatientRankings(pFile, pheno_DF, predClass, plotIt = FALSE, verbose = FALSE)

Arguments

pFile	(char) path to PRANK file
pheno_DF	(data.frame) patient IDs ('ID') and label('STATUS')
predClass	(character) class label for which predictor is built
plotIt	(logical) if TRUE plots ROC curve
verbose	(logical) print messages

Value

(list) 1) predLbl: GeneMANIA scores (predicted labels). Higher score for higher ranked patient. 2) realLbl: binary value indicating if patient label matches predictor label (real labels) 3) fullmat: pheno_DF merged with similarity scores ('similarityScore') and real label ('isPredClass') 4) roc: output of ROCRs performance(,'tpr','fpr') - ROC curve 5) auc: output of ROCRs auc() 6) precall: output of ROCRs performance(, 'prec','rec') 7) f: output of ROCRs performance(,'f') If < 2 patients in PRANK file, roc,auc, precall, f are all returned as NA.

Examples

data(pheno)
prankFile <- system.file("extdata",
paste("GM_PRANK","CV_1.query-results.report.txt.PRANK",sep=getFileSep()),
	package="netDx")
x <- getPatientRankings(prankFile, pheno, 'LumA')

BaderLab/netDx documentation built on Sept. 26, 2021, 9:13 a.m.