networkScreeningGS {WGCNA}

Network gene screening with an external gene significance measure

Description

This function blends standard and network approaches to selecting genes (or variables in general) with high gene significance

Usage

networkScreeningGS(
  datExpr,
  datME,
  GS,
  oddPower = 3,
  blockSize = 1000,
  minimumSampleSize = ..minNSamples, 
  addGS = TRUE)

Arguments

datExpr

data frame of expression data

datME

data frame of module eigengenes

GS

numeric vector of gene significances

oddPower

odd integer used as a power to raise module memberships and significances

blockSize

block size to use for calculations with large data sets

minimumSampleSize

minimum acceptable number of samples. Defaults to the default minimum number of samples used throughout the WGCNA package, currently 4.

addGS

logical: should gene significances be added to the screening statistics?

Details

This function should be considered experimental. It takes into account both the "standard" and the network measures of gene importance for the trait.

Value

GS.Weighted

weighted gene significance

GS

copy of the input gene significances (only if addGS=TRUE)

Author(s)

Steve Horvath

See Also

networkScreening, automaticNetworkScreeningGS