Hi Lev, Lev Soinov wrote: > Dear List, > On the page 49 of the LIMMA user guide there is an example of how to make a difference of differences in experiments with several factors: > > "Which genes respond differently in the mutant relative to the wild-type? > > cont.dif <- makeContrasts( > + Dif6hr =(mu.6hr-mu.0hr)-(wt.6hr-wt.0hr), > + Dif24hr=(mu.24hr-mu.6hr)-(wt.24hr-wt.6hr), > + levels=design) > > fit2 <- contrasts.fit(fit, cont.dif) > > fit2 <- eBayes(fit2) > > topTableF(fit2, adjust="BH")" > > I use a very similar code to find differences between time effects and strain effects. > I have two strains (B and W) and two different time points (2 and 1 hours). I am trying to find genes which respond differently: > 1. in B vs W, when comparing time points 1 and 2 (i.e. I compare BvsW in time point 1 to BvsW in time point 2) > 2. in time in different strains (i.e. I compare B1vsB2 versus W1vsW2) > > I am getting the same results, or they should be the same? > Could you comment on whether this is a right way to analyse time series? It appears you want to test for the interaction between time and strain. Both of your points (1 and 2 above) are essentially identical. You want to know what genes react differently over time in the two strains (and worded differently, but meaning the same thing - what genes react differently between the strains at different times). These two things are verbo-algebraically the same (yup, new word. My next move is to start a new Wikipedia entry describing exactly what it means ;-D) > > My code is below. > > > Thank you, > Lev. > > > temp<-rma(data) > > targets <- readTargets("Targets.txt") > >>lev <- c("W.1","B.1","W.2","B.2") >>f <- factor(targets$Target, levels=lev) >>design <- model.matrix(~0+f) >>colnames(design) <- lev >>fit <- lmFit(temp, design) >>cont.dif <- makeContrasts(Diff.Time=(B.2-W.2)-(B.1-W.1), Diff.Strain=(B.2-B.1)-(W.2-W.1), levels=design) As the statements above are verbo-algebraically the same, these two terms are algebraically the same. (B.2-W.2)-(B.1-W.1) = (B.2-B.1)-(W.2-W.1) Hence you should get the same results from each contrast. And yes, this contrast does give you the interaction. Best, Jim >>fit2 <- contrasts.fit(fit, cont.dif) >>fit2 <- eBayes(fit2) > > > I am getting the same results for both coefficients: > >>results<-decideTests(fit2, method="separate", p=0.01, lfc=1) >>summary(results) > > Diff.Time Diff.Strain > -1 61 61 > 0 44951 44951 > 1 89 89 > > My target file is: > FileName Target > 3517 W.1 > 3518 W.1 > 3519 W.1 > 3520 W.1 > 3521 W.1 > 3522 B.1 > 3524 B.1 > 3525 B.1 > 3526 B.1 > 3527 W.2 > 3528 W.2 > 3529 W.2 > 3530 W.2 > 3531 B.2 > 3532 B.2 > 3533 B.2 > 3534 B.2 > > > > --------------------------------- > Yahoo! Mail is the world's favourite email. Don't settle for less, sign up for your freeaccount today. -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.