callFeatSel: Return feature selected nets based on given criteria

In BaderLab/netDx: Network-based patient classifier

Description

Return feature selected nets based on given criteria

Usage

callFeatSel(netScores, fsCutoff, fsPctPass)

Arguments

netScores	(matrix) matrix of net scores
fsCutoff	(integer) net must score at least this much in a split to 'pass' the threshold
fsPctPass	(numeric 0 to 1) net must pass at least this percent of splits to be considered feature-selected

Details

given the output of genNetScores.R and criteria for defining feature-selected (FS) nets, returns subset of nets that pass criteria. Net must score <fsCutoff> for at least <fsPctPass> considered feature-selected.

Value

(char) names of nets that pass feature-selection

Examples

data(featScores)
passed <- lapply(featScores, function(x) {
   callFeatSel(x,10,0.7) # score 10/10 in >=70% of trials
})
print(passed)

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