My understanding is that CyberT doesn't handle paired t-tests, although I could be wrong. The closely related but more general method in the limma package does however. Here's a small example. First simulate data. In your case, replace Y with the exprSet object you get from gcrma(). Y <- matrix(rnorm(8912*8),8912,8) Sample <- factor(rep(1:4,each=2)) BeforeAfter <- factor(rep(1:2,length=8)) design <- model.matrix(~Sample+BeforeAfter) library(limma) fit <- lmFit(Y,design) fit <- eBayes(fit) topTable(fit, coef="BeforeAfter2", adjust="fdr") Gordon >[BioC] CyberT: Paired Bayes t-test (Bayes corrected p-values) >Groot, Philip de philip.degroot at wur.nl >Tue Jun 28 09:49:03 CEST 2005 > >Hello, > >I have been digging in Bayesreg.R for several days now, but cannot find >the solution for my problem. I want to calculate a Bayes PAIRED t-test >if this is possible (I have the impression that it is not). With a >paired t-test I am refering to a biological sample before and after >treatment from the same object. This test is performed for 4 different >objects, so in total I have 8 samples: 4 before treatment and 4 after >treatment. The samples are hybridized on a HG-U133 plus2 array and >quality control, GC-RMA normalization and IQR-filtering have been >applied. In total, 8912 genes remained for calculating the Bayes paired >p-values. > >When looking at this site: >http://visitor.ics.uci.edu/genex/cybert/help/index.html I can find an >example on how a paired Bayes t-test can be performed (that is: if I >understand it correctly): add to the original non-2log transformed data >(so transform the GC-RMA values back to the non-log scale) an additional >'Expr Est' column (my statistical background is not as such that this >makes sense to me). Well, I did this (using numR=8 and doLog=TRUE) and >calculated p-values between 0 and roughly 10^-6... Of course, this can't >be true... Searching for additional help (which is hardly available for >paired t-tests) I found a CyberT refence saying that the paired t-test >refers to the 2-dye situation. It is paired because the same array is >used. Well, in my situation (Affymetrix) this is not true, but I can >calculate the ratio after / before treatment (on the same object) and >put it in. This did make sense, but now I find p-values between 0 and >1.5! It is weird that Bayesreg.R allows the generation of p-values >larger than 1, so I am wondering whether this is an artifact of Bayesian >statistics or that I am doing something wrong? Can someone please give >me a hint on how to do the paired Bayesian t-test properly (e.g. with a >small example dataset)? > >Kind regards, > >Dr. Philip de Groot >Wageningen University