pickSIMoNeParam: Pick SIMoNe parameters

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

Description

A function to help in choosing the SIMoNe parameter, and most particularly which model criterion, with a series of plot.

Usage

pickSIMoNeParam(DEGeneExpr, ClusterMethod = F, NEdges = NA)

Arguments

DEGeneExpr	Object of class DEGeneExpr
ClusterMethod	Boolean variable indicating whether using clustering constraint or not
NEdges	If clustering constraint is used, on which number of edges to do it. 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 from network without clustering constraint.

Details

The series of plots are directly taken from the function plot() of simone package.

Note

A precaution must be taken by choosing the parameters, and the expression data matrix dimensions.

References

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

See Also

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

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.