getEMapInput_many {netDx} | R Documentation

## Wrapper to generate multiple EnrichmentMaps (perhaps one per class)

### 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())
    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)

[Package netDx version 1.0.3 Index]