WGCNA: automaticNetworkScreeningGS – R documentation

Pricing

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

Get Started for Free

Documentation

WGCNA

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

Description

This function performs gene screening based on external gene significance and their network properties.

Usage

automaticNetworkScreeningGS(
     datExpr, GS, 
     power = 6, networkType = "unsigned", 
     detectCutHeight = 0.995, minModuleSize = min(20, ncol(as.matrix(datExpr))/2), 
     datME = NULL)

Arguments

`datExpr`	data frame containing the expression data, columns corresponding to genes and rows to samples
`GS`	vector containing gene significance for all genes given in `datExpr`
`power`	soft thresholding power used in network construction
`networkType`	character string specifying network type. Allowed values are (unique abbreviations of) `"unsigned"`, `"signed"`, `"hybrid"`.
`detectCutHeight`	cut height of the gene hierarchical clustering dendrogram. See `cutreeDynamic` for details.
`minModuleSize`	minimum module size to be used in module detection procedure.
`datME`	optional specification of module eigengenes. A data frame whose columns are the module eigengenes. If given, module analysis will not be performed.

Details

Network screening is a method for identifying genes that have a high gene significance and are members of important modules at the same time. If datME is given, the function calls networkScreeningGS with the default parameters. If datME is not given, module eigengenes are first calculated using network analysis based on supplied parameters.

Value

A list with the following components:

`networkScreening`	a data frame containing results of the network screening procedure. See `networkScreeningGS` for more details.
`datME`	calculated module eigengenes (or a copy of the input `datME`, if given).
`hubGeneSignificance`	hub gene significance for all calculated modules. See `hubGeneSignificance`.

Author(s)

Steve Horvath