stringgaussnet (version 1.1)

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

Description

This function allows to create an object of class MultiNetworks from an object of class MultiDEGeneExpr. This is a wrapper of all methods available in the stringgaussnet package.

Usage

## S3 method for class 'default':
MultiNetworks(x, Methods = c("STRING", "SIMoNe", "WGCNA"), STRINGOptions = NULL,
	SIMoNeOptions = NULL, WGCNAOptions = NULL, SelectInteractionsSTRING = NULL,
	STRINGThreshold = 0, FilterShortPathOptions = NULL, FilterSIMoNeOptions = NULL,
	Factors = NULL, ...)

Arguments

x

An object of class MultiDEGeneExpr

Methods

A character vector indicating which network construction methods to use, among "STRING", "SIMoNe" and "WGCNA"

STRINGOptions

List with parameters available in the function getSTRINGNet()

SIMoNeOptions

List with parameters available in the function getSIMoNeNet()

WGCNAOptions

List with parameters available in the function getWGCNANet()

SelectInteractionsSTRING

A character vector indicating which interaction sources to select in STRINGNet. Please see selectInteractionTypes() for more details.

STRINGThreshold

Confidence score threshold for edge filtering in STRINGNet

FilterShortPathOptions

List with parameters available in the function FilterEdges.ShortPathSTRINGNet()

FilterSIMoNeOptions

List with parameters available in the function FIlterEdges.SIMoNeNet()

Factors

A vector of factors attributed to samples. Must gather all samples present in x.

...

Additional parameters. Not used here.

Value

• An object of class MultiNetworks, which is a list of different network objects. If STRING method is used, shortest paths between initial nodes are computed.

See Also

MultiNetworks, print.MultiNetworks, MultiDEGeneExpr.default

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,])

# MultiSpAData<-MultiDEGeneExpr(GaussianSpAData,DEGeneExpr(t(SpADataExpression[18:34,]),
#	SpADEGenes[18:34,]),DEGeneExpr(t(SpADataExpression[35:51,]),SpADEGenes[35:51,]))
# MultiSpANetworks<-MultiNetworks(MultiSpAData,
#	SelectInteractionsSTRING=c("coexpression","experimental","knowledge"),STRINGThreshold=0.9,
#	FilterSIMoNeOptions=list(Threshold=0.4),Factors=StatusFactor,
#	STRINGOptions=list(AddAnnotations=FALSE),SIMoNeOptions=list(AddAnnotations=FALSE),
#	WGCNAOptions=list(AddAnnotations=FALSE))