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

In stringgaussnet: PPI and Gaussian Network Construction from Transcriptomic Analysis Results Integrating a Multilevel Factor

Description

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

Usage

## Default S3 method:
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)

stringgaussnet documentation built on May 29, 2017, 10:50 a.m.