Dear Praful, DESeq >=1.9.1 in the devel branch contains a new function varianceStabilizingTransformation that returns the variance-stabilised data in an ExpressionSet, which you can then directly feed to arrayQualityMetrics, e.g. like this: library("pasilla") library("vsn") library("arrayQualityMetrics") data("pasillaGenes") cdsBlind = estimateDispersions(estimateSizeFactors(pasillaGenes), method="blind") pasillaVst = varianceStabilizingTransformation(cdsBlind) meanSdPlot(pasillaVst) arrayQualityMetrics(pasillaVst, intgroup=c("condition", "type"), force=TRUE) Let me know if this works for you. As usual, the code will need a day or two to percolate from the svn archive to the website. Kind regards Wolfgang Mar/29/12 9:53 PM, Wolfgang Huber scripsit:: > > Dear Praful > > On 3/29/12 8:00 PM, Aggarwal, Praful wrote: >> Hello Wolfgang, >> >> In your previous reply you mentioned that I "do the 6 MA -plots for >> all pairs of samples and where the hits are in there." According to >> the DESeq documentation, an MA plot was done after we get the >> foldchange using the nbinomTest. However, do you suggest trying MA >> plots using the normalized counts of all 4 samples or do you mean >> something else when you mentioned looking at the MA plots. > > Yes, you can do several things: > 1. A = average expression over all six samples and M=log fold change > between sum of the counts within groups > 2. Each pairwise MA-plot > > I was thinking of 2. I think what you refer to in the documentation is 1. > >> Also, I tried calling 'arrayQualityMetrics' on the >> variance-stabilized version with both the 'maximum' and 'fit-only' >> options. However, in both cases I get the following error : >> >> Error in function (classes, fdef, mtable) : unable to find an >> inherited method for function "platformspecific", for signature >> "matrix" >> >> I have never used arrayQualityMetrics, but even after looking at the >> function I couldn't quite understand what might be causing this >> error. Any help on this would be greatly appreciated. > > Sorry. Indeed this requires some programming on my end to make it > convenient. I'll implement this asap and will announce it here. > > Until then, if you are suffciently familiar with Bioconductor data > structures, what needs to be done is to create an ExpressionSet which > contains the data matrix, and whose featureData and phenoData are taken > from the countDataSet. This is explained in the vignette of the package > Biobase "An introduction to Biobase and ExpressionSets". > > Best wishes > Wolfgang > > > > >> Kind Regards, Praful >> >> Praful Aggarwal Broeckel Lab Human and Molecular Genetics Center >> Medical College of Wisconsin 8701 Watertown Plank Road CRI/TBRC 2nd >> Floor Milwaukee, WI 53226 >> >> 414-955-2567 >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ Bioconductor mailing >> list Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor Search the >> archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor > > -- Best wishes Wolfgang Wolfgang Huber EMBL http://www.embl.de/research/units/genome_biology/huber