runFeatureSelection: Run GeneMANIA cross-validation with a provided subset of...

In BaderLab/netDx: Network-based patient classifier

Description

Run GeneMANIA cross-validation with a provided subset of networks

Usage

runFeatureSelection(
  trainID_pred,
  outDir,
  dbPath,
  numTrainSamps = NULL,
  incNets = "all",
  orgName = "predictor",
  fileSfx = "CV",
  verbose = FALSE,
  numCores = 2L,
  JavaMemory = 6L,
  verbose_runQuery = FALSE,
  debugMode = FALSE,
  ...
)

Arguments

trainID_pred	(char) vector with universe of predictor class patients (ie all that can possibly be included in the query file
outDir	(char) directory to store query file and GM results
dbPath	(char) path to GeneMANIA generic database with training population
numTrainSamps	(integer) number of training samples in total leave blank to use 5 training samples in order to save memory
incNets	(char) vector of networks to include in this analysis (features/pathway names). Useful for subset-based feature selection
orgName	(char) organism name for GeneMANIA generic database. The default value will likely never need to be changed.
fileSfx	(char) file suffix
verbose	(logical) print messages
numCores	(logical) num parallel threads for cross-validation
JavaMemory	(integer) memory for GeneMANIA run, in Gb.
verbose_runQuery	(logical) print messages for runQuery()
debugMode	(logical) when TRUE runs jobs in serial instead of parallel and prints verbose messages. Also prints system Java calls and prints all standard out and error output associated with these calls.
...	args for makeQueries()

Details

Creates query files, runs GM for 10-fold cross validation.

Value

No value. Side effect of generating feature scores.

Examples

data(MB.pheno)
dbPath <- system.file("extdata","dbPath",package="netDx")
runFeatureSelection(MB.pheno$ID[which(MB.pheno$STATUS%in% 'WNT')],
		tempdir(),dbPath,103L)

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