Re: Any problem with the design matrix or the contrasts? Thanks
"Ryan C. Thompson" <[email protected]>
| Newsgroups | gmane.science.biology.informatics.conductor |
|---|---|
| Message-ID | <[email protected]> |
Hi, You're going to need to address your two scientific questions using separate fits. This is because your first question (pos vs neg) is testing a main effect, and you are effectively fitting an interaction model (one coefficient for each combination of AR & gender). So your interaction model is correct for testing the second question, which is testing one factor within only a single level of the other. But for testing the main effect, you'll need to fit an additive model using the formula suggested by Federico. Furthermore, the test for a main effect may not be valid in the presence of an interaction effect, so you should test for that too using the interaction model, and then look closely at the data before trusting probe sets that are significant for both the main effect and interaction effect. The interaction contrast using your design would be ((F.pos-M.pos)-(F.neg-M.neg)). -Ryan On 08/01/2014 08:07 AM, Rao,Xiayu wrote: > Hello, > > I learned from posts in the forum and analyzed my data using the suggested design and contrasts. It turns out there are no sig genes or few in the end. Could you please help check if the design does not fit the data or the contrasts made are incorrect?? > > #the research questions are 1) to compare between pos and neg for AR, and 2) Male.pos vs. Female.pos. > > Treat <- factor(paste(targets$gender,targets$AR,sep=".")) > chip <- factor(targets$chip) > design <- model.matrix(~0+Treat+chip) > colnames(design)[1:4] <- levels(Treat) > fit <- lmFit(y,design) > > cm <- makeContrasts(posVSneg=(F.pos+M.pos-F.neg-M.neg)/2, MposVSFpos=M.pos-F.pos, levels=design) > fit2 <- contrasts.fit(fit,cm) > fit2 <- eBayes(fit2) > topTable(fit2, coef="posVSneg", sort.by="p") #0 sig genes > topTable(fit2, n=20,coef="MposVSFpos", sort.by="p") #4 sig genes > > targets.txt > sample gender AR chip > s1 F pos 1 > s2 F neg 1 > s3 M neg 2 > s4 M pos 2 > s5 F neg 2 > s6 M pos 2 > s7 M pos 2 > s8 M pos 3 > s9 M pos 3 > s10 M pos 3 > s11 M pos 3 > s12 F pos 4 > s13 F pos 4 > s14 M pos 4 > s15 M pos 4 > s16 F pos 5 > s17 M pos 5 > s18 M pos 5 > s19 M neg 6 > s20 M neg 6 > s21 F neg 6 > s22 F pos 6 > s23 F pos 6 > s24 F neg 6 > s25 F pos 6 > s26 F pos 6 > s27 F pos 6 > s28 M neg 6 > > > Thanks, > Xiayu > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor _______________________________________________ Bioconductor mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor