netinf2gml: Function to create an 'igraph' object and export a network to...

In predictionet: Inference for predictive networks designed for (but not limited to) genomic data

Description

This function creates, from a network inferred from netinf or netinf.cv, an igraph object and export this network to a GML readable by Cytoscape.

Usage

netinf2gml(object, edge.info, node.info, file = "predictionet")

Arguments

object	object returns by netinf or netinf.cv
edge.info	matrix of values representing the statistics for each edge; parents in rows, children in columns. A list of matrices could be provided, names of the list will then be used to describe the statistics in Cytoscape
node.info	vector of values representing the statistics for each node; parents in rows, children in columns. A list of vectors could be provided, names of the list will then be used to describe the statistics in Cytoscape
file	name of the GML file to be saved.

Details

The GML file created by this function has been tested on Cytoscape 2.8.1; a Vizmap property file of the same name is also created and could be imported into Cytoscape ("preditionet_vizmap2") so the information for each node and edge are displayed correctly.

Value

an igraph object

Author(s)

Benjamin Haibe-Kains

See Also

\codeRCytoscape

Examples

## load gene expression data for colon cancer data, list of genes related to RAS signaling pathway and the corresponding priors
data(expO.colon.ras)
## number of genes to select for the analysis
genen <- 10
## select only the top genes
goi <- dimnames(annot.ras)[[1]][order(abs(log2(annot.ras[ ,"fold.change"])), decreasing=TRUE)[1:genen]]
mydata <- data.ras[ , goi, drop=FALSE]
myannot <- annot.ras[goi, , drop=FALSE]
mypriors <- priors.ras[goi, goi, drop=FALSE]
mydemo <- demo.ras
## infer global network from data and priors
mynet <- netinf.cv(data=mydata, categories=3, priors=mypriors, priors.count=TRUE, priors.weight=0.5, maxparents=3, method="regrnet", nfold=3, seed=54321)

## create an igraph obkect and export it into a GML file
## Not run: netinf2gml(object=mynet, file = "predictionet")

Example output

Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

Loading required package: catnet

predictionet documentation built on Nov. 8, 2020, 7:48 p.m.