WGCNA (version 1.25-1)

networkScreening: Identification of genes related to a trait

Description

This function blends standard and network approaches to selecting genes (or variables in general) highly related to a given trait.

Usage

networkScreening(y, datME, datExpr, 
                 corFnc = "cor", corOptions = "use = 'p'",
                 oddPower = 3, 
                 blockSize = 1000, 
                 minimumSampleSize = ..minNSamples,
                 addMEy = TRUE, removeDiag = FALSE, 
                 weightESy = 0.5, getQValues = TRUE)

Arguments

y

clinical trait given as a numeric vector (one value per sample)

datME

data frame of module eigengenes

datExpr

data frame of expression data

corFnc

character string specifying the function to be used to calculate co-expression similarity. Defaults to Pearson correlation. Any function returning values between -1 and 1 can be used.

corOptions

character string specifying additional arguments to be passed to the function given by corFnc. Use "use = 'p', method = 'spearman'" to obtain Spearman correlation.

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.

addMEy

logical: should the trait be used as an additional "module eigengene"?

removeDiag

logical: remove the diagonal?

weightESy

weight to use for the trait as an additional eigengene; should be between 0 and 1

getQValues

logical: should q-values be calculated?

Value

• datout = data.frame(p.Weighted, q.Weighted, Cor.Weighted, Z.Weighted, p.Standard, q.Standard, Cor.Standard, Z.Standard) Data frame reporting the following quantities for each given gene:
• p.Weighted
  weighted p-value of association with the trait
• q.Weighted
  q-value (local FDR) calculated from p.Weighted
• cor.Weighted
  correlation of trait with gene expression weighted by a network term
• Z.Weighted
  Fisher Z score of the weighted correlation
• p.Standard
  standard Student p-value of association of the gene with the trait
• q.Standard
  q-value (local FDR) calculated from p.Standard
• cor.Standard
  correlation of gene with the trait
• Z.Standard
  Fisher Z score of the standard correlation

Details

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