getEMapInput_many: Wrapper to generate multiple EnrichmentMaps (perhaps one per...

In netDx: Network-based patient classifier

Description

Wrapper to generate multiple EnrichmentMaps (perhaps one per class)

Usage

getEMapInput_many(featScores, namedSets_valid, netTypes, outDir, ...)

Arguments

featScores	(list) keys are classes, and values are data.frames of network scores across cross-validation (output of getFeatScores()).
namedSets_valid	(list) Grouped unit variables limited to the units contained in the dataset. e.g. keys are pathways and values are the genes measured in this dataset. e.g.: $'MISSPLICED_GSK3BETA_MUTANTS_STABILIZE_BETA-CATENIN' [1] 'PPP2R5E' 'PPP2CB' 'APC' 'AXIN1' 'PPP2R1B' 'PPP2R1A' 'CSNK1A1' [8] 'PPP2R5D' 'PPP2R5C' 'PPP2R5B' 'PPP2R5A' 'PPP2CA' 'GSK3B'
netTypes	(data.frame) 'inputNets.txt' file generated by NetDx. Dataframe has two columns, network type and network name. I.E: clinical clinical rna GUANOSINE_NUCLEOTIDES__I_DE_NOVO__I__BIOSYNTHESIS rna RETINOL_BIOSYNTHESIS
outDir	(char) path to output directory
...	parameters for getEMapInput()

Value

(list) of length g, where g is the number of groups in featScores. Values are lists, corresponding to the output of getEmapInput.R

Examples

data(featScores)

pathwayList <- readPathways(fetchPathwayDefinitions("October",2020))
pathwayList <- pathwayList[seq_len(5)]

netInfoFile <- system.file("extdata","example_output/inputNets.txt",package="netDx")
netTypes <- read.delim(netInfoFile,sep='\t',h=FALSE,as.is=TRUE)
outDir <- paste(tempdir(),'plots',sep='/')
if (!file.exists(outDir)) dir.create(outDir)
EMap_input <- getEMapInput_many(featScores,pathwayList,
     netTypes,outDir=outDir)

netDx documentation built on Dec. 11, 2020, 2:01 a.m.