Hello all, Again, a very na?ve question regarding the analysis of my data which I am performing following some of the scripts imparted during the Milan BioC course. I'm trying to obtain differentially expressed genes from a subset of data (3 CONTROL files and 2 PROBLEM files) by assigning scores and cutoffs. But I encounter the following problem when I try: > rmadata3$Genotype [1] CONT CONT CONT VAV VAV Levels: CONT VAV > Index1 <- which(rmadata3$Genotype=="CONT") > Index2 <- which(rmadata3$Genotype=="VAV") > scores <- esApply (rmadata3, 1, function(x) { + tmp <-t.test(x[Index2], x[Index1], var.equal =TRUE) + c(mean(tmp$estimate), -diff(tmp$estimate), tmp$statistic, tmp$p.value) + }) > scores <- t(scores) > colnames(scores) <- c("a", "m", "t.test", "p.value") > plot(scores[,1], scores[,2], xlab = "A", ylab = "M", pch =".") > abline(h= c(-1, 1)) > plot(scores[,2], abs(scores[,3]), xlab = "M", ylab ="t.test", pch = ".") > abline(v= c(-1, 1)) > a <- qt(0.975, 4) > abline(h = a) > sum(scores[, 4] <= 0.05) [1] NA > sum(scores[, 4] <= 0.01) [1] NA I have tried this with a balanced set of data (3 CONT, 3 PROB) with no problems whatsoever. I wonder if this is then due to the fact that the data set is unbalanced for the number of CONT and PROB samples. If this is the case, how could I go on about it? Thanks in advance for your help, Fatima _______ ? ? F?tima N??ez, PhD Centre for Cancer Research (CIC) University of Salamanca-CSIC Campus Unamuno 37007 Salamanca?????????????????????????????????????????????????? Spain Phone: + 34 923 294802 Fax:?????+ 34 923 294743 E-mail: fnunez@usal.es