how to design a model matrix my data is composed of 35 samples, have two factor time and treatment i want to find DE genes cross the time, considering control so do you think my model matrix is right? and how to do the test?can i only do pairewised test? what is glmLRT for? this is my code rm(list=ls()) library(edgeR) library(limma) raw.data <- read.table("expression-table.txt",row.names=1)# d <- raw.data[, 1:12]# dge<- DGEList(d) treatment=factor(c(rep('treated',24),rep('control',11))) time=factor( c('oh','oh','oh','6h','6h','6h','6h','12h', '12h','12h','12h','18h','18h','18h','18h','24h','24h','24h','36h','36h ','36h','48h','48h','48h','oh', 'oh','oh','6h','12h','18h','24h','36h','48h')) design <- model.matrix(~treatment+time) dge <- estimateGLMCommonDisp(dge, design) dge <- estimateGLMTagwiseDisp(dge, design) glmfit.dge <- glmFit(dge, design,dispersion=dge$common.dispersion) lrt.dge <- glmLRT(dge, glmfit.dge, coef=2) how to design a model matrix my data is composed of 35 samples, have two factor time and treatment i want to find DE genes cross the time, considering control so do you think my model matrix is right? and how to do the test?can i only do pairewised test? what is glmLRT for? -- 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