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iClusterPlus no significant results

Hello,

Is anyone familiar with iClusterPlus?

I have been trying to use iClusterPlus to integrate methylation and expression data I have, but It's not clear to me what I might be doing wrong:

I am using beta values and RPKMS.

1) I filter out genes with low rpkm variability and probes (cpgs) with low beta value variability using kOverA function. 2) I use the tuning function to select the better results like:

set.seed(123)

   for(k in 1:5){
    cv.fit = tune.iClusterPlus(cpus=2,dt1=as.matrix(methx),dt2=as.matrix(exprx),
                                type=c("gaussian","poisson"),K=k,n.lambda=35,
                                 scale.lambda=c(1,1,1),maxiter=20)  
   save(cv.fit, file=paste("cv.fit.k",k,".Rdata",sep=""))
  }

3) My % of explained variation plot depending on the number of clusters is an increasing plot, (the more number of clusters, the most % explained variation), so maybe I should try more clusters than only 5, so I could see a better classification.

4) The clusters generated are shown in a heatmap: I can see the CpGs variation but for expression, the heatmap is almost everything the same color. Might this mean that I am filtering way too many genes?

I am using 17798 genes and 244 cpgs (maybe I need more cpgs)

How can I select the genes and probes belonging to each cluster? I can't seem to find the way by looking at the manual, everytime I get the same genes and probes.

Thank you so much.

rna-seq methyl-seq data integration omics

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