## 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")
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