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? Many thanks in advance! Kind regards, Inge -- View this message in context: http://r.789695.n4.nabble.com/wgcna-tp3649354p4633514.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
