hello all i have such coding raw.data <- read.table("expression-table.txt",row.names=1)# lib_size <- read.table("lib_size.txt"); lib_size <- unlist(lib_size) # d <- DGEList(counts = raw.data, lib.size = lib_size) dge <- d[rowSums(d$counts) >= length(lib_size)/2,]# #normalization dge <- calcNormFactors(dge) treatment=factor(c(rep('control',6),rep('treated',24),rep('control',5) )) time=factor(c('0h','0h','0h','24h','24h','24h','0h','0h','0h','6h','6h ','6h','6h','12h','12h','12h','12h','18h','18h','18h','18h', '24h','24h','24h','36h','36h','36h','48h','48h','48h','6h ','12h','18h','36h','48h')) design <- model.matrix(~time+treatment*time) # dge <- estimateGLMCommonDisp(dge, design) dge <- estimateGLMTagwiseDisp(dge, design) glmfit.dge <- glmFit(dge, design,dispersion=dge$common.dispersion) lrt.dge <- glmLRT(dge, glmfit.dge, coef=2) my question is how can estimateGLMCommonDisp be used to get the common dispersion, the glm is only used to get the regression coefficients. -- 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