stringgaussnet (version 1.1)

getWGCNANet: Infer WGCNA network from expression data

Description

This function infers a WGCNA network from expression data. This gives a gaussian network simply by filtering on correlations between expressions of each pair of genes. Dissimilarities and modules computations are not implemented, because the main purpose is to compare with SIMoNe results.

Usage

getWGCNANet(DEGeneExpr, SoftThreshold = 8, AThreshold = 0.85, AddAnnotations = F,
	MartDataset = "hsapiens_gene_ensembl")

Arguments

DEGeneExpr

Object of class DEGeneExpr. See DEGeneExpr.default() for more details.

SoftThreshold

Soft threshold parameter (alpha) used for adjacency computation by sigmoid function. See pickWGCNAParam() for some help.

AThreshold

Threshold on adjacency score for edges inference. Generally it is 0.85.

AddAnnotations

Boolean variable indicating whether gene annotations must be added through biomaRt

MartDataset

Which mart dataset to use for querying gene annotations through biomaRt. See getMartDatasets() for some help.

Value

• An object of class WGCNANet. See WGCNANet.default() for more details.

See Also

WGCNANet, WGCNANet.default, print.WGCNANet, summary.WGCNANet, export.WGCNANet, pickWGCNAParam, compareGaussNetworks

Examples

# data(SpADataExpression)
# data(SpADEGenes)
# SpAData<-DEGeneExpr(t(SpADataExpression),SpADEGenes)

# NodesForSIMoNe<-rownames(SpADEGenes)[1:17]
# GaussianSpAData<-DEGeneExpr(t(SpADataExpression[NodesForSIMoNe,]),SpADEGenes[NodesForSIMoNe,])

# pickWGCNAParam(GaussianSpAData)
# GlobalWGCNANet<-getWGCNANet(GaussianSpAData)
# print(GlobalWGCNANet,5)
# summary(GlobalWGCNANet)
# plot(GlobalWGCNANet)
# export(GlobalWGCNANet,"GlobalWGCNANet",T)

# compareGaussNetworks(GlobalSIMoNeNet,GlobalWGCNANet,c("SIMoNe","WGCNA"))