networkScreening: Identification of genes related to a trait

In WGCNA: Weighted Correlation Network Analysis

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?

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

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

Author(s)

Steve Horvath

WGCNA documentation built on Sept. 18, 2024, 5:08 p.m.