hi Sindree, The section you refer to in the limma guide is treating the patient effect as a random effect, which is not the approach of DESeq2. If you want to use a particular limma approach on RNA-Seq data, you should check out the ?voom function in the limma package. Mike On Fri, Oct 18, 2013 at 1:20 PM, Sindre Lee wrote: > Hi! > I have two groups at two time points. And the samples are the same in both > time points. I have run this in DESeq2: > > sampleFiles <- list.files(path="/Volumes/**timemachine/HTseq_DEseq2",** > pattern="*.txt"); > status <- factor(c(rep("Healthy",26), rep("Diabetic",22))) > timepoints = as.factor(c(1,1,1,1,1,1,1,1,1,** > 1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,**2,2,1,1,1,1,1,1,1,1,1,1,1,2,2,** > 2,2,2,2,2,2,2,2,2)); > sampleTable <- data.frame(sampleName = sampleFiles, fileName = > sampleFiles, status=status, timepoints=timepoints); > directory <- c("/Volumes/timemachine/HTseq_**DEseq2/"); > des <- formula(~timepoints+status); > ddsHTSeq <- DESeqDataSetFromHTSeqCount(**sampleTable = sampleTable, > directory = directory, design= des); > ddsHTSeq > > This is however not correct. > > When looking at the Limma manual page 49: http://www.bioconductor.org/** > packages/2.12/bioc/vignettes/**limma/inst/doc/usersguide.pdf > > This example is perfect for my experiment, but "Tissue = A or B" should be > "Timepoint = 1 or 2". > > So timepoint = 1 or 2 = Paired data, and Disease vs Normal = unpaired data. > > I want to compare both within and between samples, so how can I do this in > DESeq2? > > sampleTable >> > sampleName fileName status timepoints > 1 D104.txt D104.txt Healthy 1 > 2 D121.txt D121.txt Healthy 1 > 3 D153.txt D153.txt Healthy 1 > 4 D155.txt D155.txt Healthy 1 > 5 D161.txt D161.txt Healthy 1 > 6 D162.txt D162.txt Healthy 1 > 7 D167.txt D167.txt Healthy 1 > 8 D173.txt D173.txt Healthy 1 > 9 D176.txt D176.txt Healthy 1 > 10 D177.txt D177.txt Healthy 1 > 11 D179.txt D179.txt Healthy 1 > 12 D204.txt D204.txt Healthy 1 > 13 D221.txt D221.txt Healthy 1 > 14 D253.txt D253.txt Healthy 2 > 15 D255.txt D255.txt Healthy 2 > 16 D261.txt D261.txt Healthy 2 > 17 D262.txt D262.txt Healthy 2 > 18 D267.txt D267.txt Healthy 2 > 19 D273.txt D273.txt Healthy 2 > 20 D276.txt D276.txt Healthy 2 > 21 D277.txt D277.txt Healthy 2 > 22 D279.txt D279.txt Healthy 2 > 23 N101.txt N101.txt Healthy 2 > 24 N108.txt N108.txt Healthy 2 > 25 N113.txt N113.txt Healthy 2 > 26 N170.txt N170.txt Healthy 2 > 27 N171.txt N171.txt Diabetic 1 > 28 N172.txt N172.txt Diabetic 1 > 29 N175.txt N175.txt Diabetic 1 > 30 N181.txt N181.txt Diabetic 1 > 31 N182.txt N182.txt Diabetic 1 > 32 N183.txt N183.txt Diabetic 1 > 33 N186.txt N186.txt Diabetic 1 > 34 N187.txt N187.txt Diabetic 1 > 35 N188.txt N188.txt Diabetic 1 > 36 N201.txt N201.txt Diabetic 1 > 37 N208.txt N208.txt Diabetic 1 > 38 N213.txt N213.txt Diabetic 2 > 39 N270.txt N270.txt Diabetic 2 > 40 N271.txt N271.txt Diabetic 2 > 41 N272.txt N272.txt Diabetic 2 > 42 N275.txt N275.txt Diabetic 2 > 43 N281.txt N281.txt Diabetic 2 > 44 N282.txt N282.txt Diabetic 2 > 45 N283.txt N283.txt Diabetic 2 > 46 N286.txt N286.txt Diabetic 2 > 47 N287.txt N287.txt Diabetic 2 > 48 N288.txt N288.txt Diabetic 2 > > The commands used in Limma (still at page 49): > > targets <- readTargets("/Volumes/**timemachine/HTseq_DEseq2/** > Targets.rtf"); > Treat <- factor(paste(targets$status,**targets$timepoints,sep=".")); > design <- model.matrix(~0+Treat); > colnames(design) <- levels(Treat) > > So how can I create the "Targets.rtf" file? And is these commands the same > when using DESeq2? > > Thank you so much! > > ______________________________**_________________ > Bioconductor mailing list > 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]]