Dear Gordon, Thank you so much for your comments. I have updated my code and get the different results for TMM and Upper quartile normalization methods. I have two more question regarding the normalization issue. I have tried different normalization methods and would like to compare their performance. My questions are: 1. In the users' guide 2.5.6, it mentions that normalization takes the form of correction factors that enter into the statistical model. Such correction factors are usually computed internally by edgeR functions, but it is also possible for a user to supply them.I would like to supply the correct factor to edgeR, how could I do this? 2. I also would like to compare the testing results of normalized data with the results of raw data (without normalizing the data)? Could I just skip the the normalization step as below? group<-paste(L,S,R,sep=".") design<-model.matrix(~L+R+S+L:R+L:S+R:S+L:R:S) y<-DGEList(counts=counts,group=group) #y<-calcNormFactors(y,method="upperquartile",p=0.75) ##skip this step y<-estimateGLMCommonDisp(y,design) y<-estimateGLMTagwiseDisp(y,design) fiteUQ_LRS<-glmFit(y,design,offset=offset ) Thanks. Yanzhu -- output of sessionInfo(): sessionInfo() R version 3.0.1 (2013-05-16) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] DESeq_1.12.1 lattice_0.20-15 locfit_1.5-9.1 Biobase_2.20.1 BiocGenerics_0.6.0 edgeR_3.2.4 limma_3.16.8 loaded via a namespace (and not attached): [1] annotate_1.38.0 AnnotationDbi_1.22.6 DBI_0.2-7 genefilter_1.42.0 geneplotter_1.38.0 grid_3.0.1 [7] IRanges_1.18.4 RColorBrewer_1.0-5 RSQLite_0.11.4 splines_3.0.1 stats4_3.0.1 survival_2.37-4 [13] XML_3.98-1.1 xtable_1.7-1 -- Sent via the guest posting facility at bioconductor.org.

> Date: Fri, 7 Feb 2014 07:25:17 -0800 (PST) > From: "Yanzhu [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, mlinyzh at gmail.com > Subject: [BioC] EdgeR multi-factor testing questions > > > Dear Gordon, > > Thank you so much for your comments. I have updated my code and get the > different results for TMM and Upper quartile normalization methods. > > I have two more question regarding the normalization issue. I have tried > different normalization methods and would like to compare their > performance. My questions are: > > 1. In the users' guide 2.5.6, it mentions that normalization takes the > form of correction factors that enter into the statistical model. Such > correction factors are usually computed internally by edgeR functions, > but it is also possible for a user to supply them.I would like to supply > the correct factor to edgeR, how could I do this? Just enter in your own values: y$samples$norm.factors <- yourvalues > 2. I also would like to compare the testing results of normalized data > with the results of raw data (without normalizing the data)? Could I > just skip the the normalization step as below? Yes. Gordon > group<-paste(L,S,R,sep=".") > design<-model.matrix(~L+R+S+L:R+L:S+R:S+L:R:S) > y<-DGEList(counts=counts,group=group) > #y<-calcNormFactors(y,method="upperquartile",p=0.75) ##skip this step > > y<-estimateGLMCommonDisp(y,design) > y<-estimateGLMTagwiseDisp(y,design) > > fiteUQ_LRS<-glmFit(y,design,offset=offset ) > > Thanks. > > > Yanzhu > > > -- output of sessionInfo(): > > sessionInfo() > R version 3.0.1 (2013-05-16) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 > [4] LC_NUMERIC=C LC_TIME=English_United States.1252 > > attached base packages: > [1] parallel stats graphics grDevices utils datasets methods base > > other attached packages: > [1] DESeq_1.12.1 lattice_0.20-15 locfit_1.5-9.1 Biobase_2.20.1 BiocGenerics_0.6.0 edgeR_3.2.4 limma_3.16.8 > > loaded via a namespace (and not attached): > [1] annotate_1.38.0 AnnotationDbi_1.22.6 DBI_0.2-7 genefilter_1.42.0 geneplotter_1.38.0 grid_3.0.1 > [7] IRanges_1.18.4 RColorBrewer_1.0-5 RSQLite_0.11.4 splines_3.0.1 stats4_3.0.1 survival_2.37-4 > [13] XML_3.98-1.1 xtable_1.7-1 ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}