On Fri, Jun 15, 2012 at 8:04 AM, Ingezz <irholt...@gmail.com> wrote: > Dear Peter, > > I am trying to apply the WGCNA meta-analysis for two (or more) microarray > datasets-tutorial to my own data. > >> mp=modulePreservation(multiExpr,multiColor,referenceNetworks=1,verbose=3,networkType="signed", >> nPermutations=30,maxGoldModuleSize=100,maxModuleSize=400) > > However, the error I am getting is: > > Error in .checkExpr(multiData, verbose, indent) : > The submitted 'multiExpr' data contain genes or samples > with zero variance or excessive counts of missing entries. > Please use the function goodSamplesGenes on each set to filter out the > problematic > genes and samples before running modulePreservation. > > Seems pretty clear, but applying goodSamplesGenes function results in no > exclusions for both arrays. > >> GM2 <- goodSamplesGenes(M2, minFraction = 1/2, minNSamples =8, minNGenes >> =20) > > What could be the issue here? Should I increase the stringency? What > stringency should be used with goodsamplegenes for modulepreservation to > work?
Hi Inge, first, I suggest that in the future you contact me directly, since others on this list probably have no idea what we're talking about. It is difficult to diagnose the problem without the data. I suggest you specify the verbose argument to both functions with a high value (e.g., 5) which should produce more informative output. I assume you are aware of the fact that the function goodSamplesGenes returns a list whose component allOK determines whether any genes or samples should be removed. Other components in the list specify which genes and/or samples should be removed. The actual removal needs to be done by you (I haven't written a function to do that yet but may do so in the future to make it more convenient). In this sense the error message is a bit misleading and I will change that as well. HTH, Peter ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
