stringgaussnet (version 1.1)

FactorNetworks.default: Function to create an object of class FactorNetworks

Description

This function allows to infer multiple gaussian networks from a single DEGeneExpr object with a factor attributed to samples.

Usage

## S3 method for class 'default':
FactorNetworks(x, Factor, method = "SIMoNe", options = NULL, ...)

Arguments

x

An object of class DEGeneExpr

Factor

A factor attributed to samples. Names must fit with sample names. If it is a character vector, it is automatically converted to a factor.

method

Which method for gaussian network inference to use. Can be either "SIMoNe" or "WGCNA".

options

A list giving options for the gaussian network inference method. Each name corresponds to the parameters of the function getSIMoNeNet() or getWGCNANet().

...

Additional parameters. Not used here.

Value

• An object of class FactorNetworks, which is a list of gaussian networks for each level of the given factor.

See Also

FactorNetworks, print.FactorNetworks, FilterEdges.FactorNetworks, addFactorGraphsToCytoscape

Examples

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

# StatusFactor<-paste(SpASamples$status,SpASamples$b27,sep=".")
# names(StatusFactor)=SpASamples$chipnum

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

# GlobalSIMoNeNetNF<-getSIMoNeNet(GaussianSpAData)
# GlobalSIMoNeNet<-FilterEdges(GlobalSIMoNeNetNF,0.4)

# StatusFactorSIMoNeNet<-FactorNetworks(GaussianSpAData,StatusFactor,"SIMoNe")
# StatusFactorSIMoNeNet<-FilterEdges(StatusFactorSIMoNeNet,0.4)

# resetCytoscapeSession()
# addNetworkStyle("SIMoNeNet",class(GlobalSIMoNeNet),points.size.map="P.Value",
# points.fill.map="logFC")
# addFactorGraphsToCytoscape(StatusFactorSIMoNeNet)