dear all: i have a question how to design model in DESeq. my data is composed of 35 samples, have two factor time and treatment i want to find DE genes cross the time, considering control how to design the model? such is my coding. counts <- read.table("expression-table.txt",row.names=1) design<- data.frame(row.names=colnames(counts), treatment= c(rep('control',6),rep('treated',24),rep('control',5)), time= c('0h','0h','0h','24h','24h','24h','0h','0h','0h','6h','6h','6h','6h', '12h','12h','12h','12h','18h','18h','18h','18h', '24h','24h','24h','36h','36h','36h','48h','48h','48h','6h ','12h','18h','36h','48h')) cds <- newCountDataSet(counts, design cds <- estimateSizeFactors(cds) cds <- estimateDispersions(cds) fit1 <-fitNbinomGLMs(cds, count ~ treatment + time) fit0 <-fitNbinomGLMs(cds, count ~ treatment) pvalsGLM <-nbinomGLMTest(fit1, fit0) padjGLM <-p.adjust(pvalsGLM, method = "BH") -- shan gao Room 231(Dr.Fei lab) Boyce Thompson Institute Cornell University Tower Road, Ithaca, NY 14853-1801 Office phone: 1-607-254-1267(day) Official email:sg839 at cornell.edu Facebook:http://www.facebook.com/profile.php?id=100001986532253