Hi Jim and All, Thanks really a lot for bringing that to my attention. It didn't work this way as well as I had different number of samples for each Phenotype unlike the edgeR example which had 3 patients for each "Disease" category. But, I took off the empty columns from the design matrix and it worked. Is the analysis done correctly this way ? I have one more doubt - Would it be possible to account for batch effect too with this type of design matrix ? Like this: design=model.matrix(~Phenotype+Phenotype:pair+ Phenotype:Treat+Phenotype:batch) Thanks, Preethy On Fri, Apr 25, 2014 at 8:00 PM, James W. MacDonald <jmacdon@uw.edu> wrote: > Hi Preethy, > > You need to re-read that section of edgeR, and in particular look at the > patient column of the revised targets frame. > > Best, > > Jim > > > > On 4/25/2014 12:46 PM, Preethy Venkat Ram wrote: > >> Hi Jim, >> >> Thanks for the reply. I've tried that - with a slighlty modified code. I >> am sorry. But, I'm getting error again. >> >> Here: >> >> pair=factor(rep(c(1:45), each=2)).Treat=factor( rep(c("Before", >> "After"),45), levels=c("Before", "After")) >> Phenotype=factor(rep(c(1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, >> 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, >> 2, 1, 2, 2), each=2),levels=c("1","2")) >> design=model.matrix(~Phenotype+Phenotype:pair+Phenotype:Treat) >> colnames(design) >> counts.DGEList<-DGEList(counts, group=Treat) >> y<-calcNormFactors(counts.DGEList) >> y<-estimateCommonDisp(y, design) >> y<-estimateGLMTrendedDisp(y, design) >> >> >> The error message here: >> >> > y<-estimateGLMTrendedDisp(y, design) >> Error in return(NA, ntags) : multi-argument returns are not permitted >> In addition: Warning message: >> In estimateGLMTrendedDisp.default(y = y$counts, design = design, : >> No residual df: cannot estimate dispersion >> >> >> One reason I can see is that the number of columns in my design matrix >> is "92" as they are more replicates/patients than in the 3.5 example. And >> there are only "90" columns in my "count" matrix. >> >> But, do you have any idea how can I solve this ? >> >> Thanks, >> Preethy >> >> >> >> >> >> On Fri, Apr 25, 2014 at 6:45 PM, James W. MacDonald <jmacdon@uw.edu<mailto:>> jmacdon@uw.edu>> wrote: >> >> Hi Preethy, >> >> This experiment is very similar to the example in part 3.5 of the >> edgeR User's guide, starting on page 31. >> >> Best, >> >> Jim >> >> >> >> On 4/25/2014 11:29 AM, Preethy Venkat Ram wrote: >> >> Hi Devon, >> >> Thanks for the replies both on biostars and here. Sorry for >> crossposting. Both >> mailing lists and discussion have been very helpful to me. >> >> But, I rarely see replies from BioC package maintainers at >> biostars. >> >> All the samples are paired and I have them all correct - I >> mean none of >> them are empty >> I tried different designs. But ending up with the same error >> message. >> What I want to do: Getting DE genes between >> (Phenotype1.Before-Phenotype1.After) & >> (Phenotype2.Before-Phenotype2.After) >> >> pdata here: >> >> pair=rep(c(1:45), each=2) >> Treat=rep(c("Before", "After"),45) >> Phenotype=rep(c(1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, >> 2, 2, 2, 2, >> 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, >> 1, 2, 2, 1, 2, >> 2), each=2) >> pdata<-data.frame(pair,Treat,Phenotype) >> >> >> Preethy >> >> >> >> On Fri, Apr 25, 2014 at 4:53 PM, Devon Ryan <dpryan@dpryan.com>> <mailto:dpryan@dpryan.com>> wrote: >> >> Hi Preethy, >> >> You likely want: >> >> design=model.matrix(~pair+Treat:Phenotype, data=pdata) >> >> If that still yields the error, then you'll need to share >> "pdata" or >> "design". Also, please don't crosspost on both this list >> and biostars ( >> https://www.biostars.org/p/98907/), it duplicates the >> community effort. >> >> Devon >> >> >> -- >> Devon Ryan, Ph.D. >> Email: dpryan@dpryan.com <mailto:dpryan@dpryan.com> >> >> Laboratory for Molecular and Cellular Cognition >> German Centre for Neurodegenerative Diseases (DZNE) >> Ludwig-Erhard-Allee 2 >> 53175 Bonn >> Germany >> <devon.ryan@dzne.de <mailto:devon.ryan@dzne.de="">> >> >> >> >> >> On Fri, Apr 25, 2014 at 11:15 AM, Preethy [guest] >> <guest@bioconductor.org <mailto:guest@bioconductor.org="">> >>wrote: >> >> >> Hi All, >> >> I had been trying to do DE analysis of my RNAseq >> experiment using edgeR >> and am having some isssues. The details of the >> Experiment and the R code I >> tried below: >> >> (a) Paired experimental design with 45 pairs >> (b) Treatment: "Before" and "After" >> (c) Phenotype: 1 & 2 >> Aim: Look for DE genes between Phenotype 1 and 2 upon >> treatment taking >> into account the paired design >> >> The R code tried: >> >> library(edgeR) >> counts<-read.delim(file="counts.dat",header=T) >> pair=factor(pdata$pair) >> Treat=factor( pdata$treat) >> Phenotype=factor(pdata$pheno) >> group<-paste(Treat,Phenotype,sep=".") >> design=model.matrix(~pair+Treat:Phenotype, data=counts) >> counts.DGEList<-DGEList(counts, group=group) >> y<-calcNormFactors(counts.DGEList) >> y<-estimateCommonDisp(y, design) >> y<-estimateGLMTrendedDisp(y, design) >> >> >> Error message I get: >> >> Error in glmFit.default(y, design = design, dispersion >> = dispersion, >> offset = offset, : >> Design matrix not of full rank. The following >> coefficients not >> estimable: >> TreatBefore:Phenotype1 TreatBefore:Phenotype2 >> >> >> Any idea to solve this out? >> >> Thanks, >> Preethy >> >> -- output of sessionInfo(): >> >> R version 3.1.0 (2014-04-10) >> Platform: x86_64-pc-linux-gnu (64-bit) >> >> locale: >> [1] LC_CTYPE=fi_FI.UTF-8 LC_NUMERIC=C >> [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8 >> [5] LC_MONETARY=fi_FI.UTF-8 LC_MESSAGES=en_GB.UTF-8 >> [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C >> [9] LC_ADDRESS=C LC_TELEPHONE=C >> [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C >> >> attached base packages: >> [1] stats graphics grDevices utils datasets >> methods base >> >> other attached packages: >> [1] edgeR_3.4.2 limma_3.18.13 >> >> >> -- >> Sent via the guest posting facility at >> bioconductor.org <http: bioconductor.org="">. >> >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> <mailto:bioconductor@r-project.org> >> >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics. >> conductor >> >> >> [[alternative HTML version deleted]] >> >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org <mailto:bioconductor@r-project.org> >> >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> >> >> -- James W. MacDonald, M.S. >> Biostatistician >> University of Washington >> Environmental and Occupational Health Sciences >> 4225 Roosevelt Way NE, # 100 >> Seattle WA 98105-6099 >> >> >> > -- > James W. MacDonald, M.S. > Biostatistician > University of Washington > Environmental and Occupational Health Sciences > 4225 Roosevelt Way NE, # 100 > Seattle WA 98105-6099 > > [[alternative HTML version deleted]]