getSIMoNeNet: Infer SIMoNe network from expression data

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

Description

This function infers a SIMoNe network from expression data. This gives a non-supervised gaussian network with partial correlation computations.

Usage

getSIMoNeNet(DEGeneExpr, NEdges = NA, ClusterMethod = "both", AddAnnotations = F,
	MartDataset = "hsapiens_gene_ensembl")

Arguments

DEGeneExpr	Object of class DEGeneExpr
NEdges	Criter selection of SIMoNe model. Can be the number of edges, 'BIC' or 'AIC'. If it is set to NA, the function chooses the number of edges by computing the mean between those with maximal AIC and BIC scores.
ClusterMethod	Can be TRUE, FALSE, or 'both'. If it is set to 'both', the function computes networks with and without clustering constraints, and pick common edges between the both.
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 SIMoNeNet. See SIMoNeNet.default() for more details.

Note

A precaution must be taken by choosing the parameters, and the expression data matrix dimensions. You can use pickSIMoNeParam() to help in the choice of parameters.

References

Chiquet, J. et al. SIMoNe Statistical Inference for MOdular NEtworks. Bioinforma. Oxf. Engl. 25, 417 (2009).

See Also

SIMoNeNet, SIMoNeNet.default, print.SIMoNeNet, summary.SIMoNeNet, export.SIMoNeNet, FilterEdges.SIMoNeNet, pickSIMoNeParam

Examples

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

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

# pickSIMoNeParam(GaussianSpAData)

# GlobalSIMoNeNet<-getSIMoNeNet(GaussianSpAData)
# GlobalSIMoNeNet<-FilterEdges(GlobalSIMoNeNet,0.4)
# print(GlobalSIMoNeNet,5)
# summary(GlobalSIMoNeNet)
# plot(GlobalSIMoNeNet)

# export(GlobalSIMoNeNet,"GlobalSIMoNeNet",T)

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