HTSanalyzeR (version 2.24.0)

networkPlot: Plot the enriched subnetwork

Description

This function takes in a subnetwork module resulted from the function networkAnalysis, a vector of labels for nodes in the module and a phenotype vector (optional) to generate a figure.

Usage

networkPlot(nwAnalysisOutput, phenotypeVector=NULL)

Arguments

nwAnalysisOutput

a list consisting of 'subnw' and 'labels', in which 'subnw' is the subnetwork module generated by the function networkAnalysis, while 'labels' is a character vector specifying the labels for all nodes in the module.

phenotypeVector

a numeric or integer vector characterizing the phenotypes of nodes in the subnetwork module.

Value

a subnetwork module of class graphNEL

Details

The 'phenotypeVector' argument is optional. The subnetwork figure will be more readable if it is provided. See the function plotModule function in the 'BioNet' package for more details.

References

Beisser D, Klau GW, Dandekar T, Muller T, Dittrich MT. BioNet: an R-Package for the functional analysis of biological networks. Bioinformatics. 2010 Apr 15;26(8):1129-30.

Dittrich MT, Klau GW, Rosenwald A., Dandekar T and Muller T. Identifying functional modules in protein-protein interaction networks: an integrated exact approach. Bioinformatics 2008 24(13):i223-i231.

See Also

networkAnalysis, viewSubNet, plotSubNet

Examples

## Not run: 
# library(BioNet)
# library(org.Dm.eg.db)
# ##load pvalues, interactome, and phenotype vector (see the vignette for
# ##preprocessing details about this dataset)
# data("KcViab_PVals", "Biogrid_DM_Interactome", "KcViab_Data4Enrich")
# ##Identify subnetworks
# enrichedSubNet <- networkAnalysis(pvalues=KcViab_PVals,
# graph=Biogrid_DM_Interactome, fdr=0.001, verbose=TRUE)
# dev.off()
# map <- as.list(get("org.Dm.egSYMBOL"))
# labels <- map[nodes(enrichedSubNet)]
# nwAnalysisResult <- list(subnw=enrichedSubNet, labels=labels)
# networkPlot(nwAnalysisOutput=nwAnalysisResult, phenotypeVector= 
# KcViab_Data4Enrich) 
# ## End(Not run)