Dear Smyth, Hello, I'm curious about how p-value is calculated (or which degree of freemdom is used) from the R example of the function lm.series in the package "limma" below. [R Example as in help page] M <- matrix(rnorm(100*6,sd=0.3),100,6) M[1,1:3] <- M[1,1:3] + 2 # Design matrix includes two treatments, # one for first 3 and one for last 3 arrays design <- cbind(First3Arrays=c(1,1,1,0,0,0),Last3Arrays=c(0,0,0,1,1,1)) fit <- lm.series(M,design=design) eb <- ebayes(fit) # Large values of eb$t indicate differential expression qqt(eb$t[,1],df=fit$df+eb$df.prior) abline(0,1) I thought following two codes should give same results, but they didn't. Which degree of freedom should I use to get the same p.value? eb$p.value[1,1] 1-pt(eb$t[1,1], fit$df[1]+eb$df.prior) Thank you. Jihoon Kim