I am a newcomer to DNA microarrays and I have recently been playing around with the swirl dataset that is available through the bioconductor R package. I have seen some results regarding the swirl data set on the internet that have used one-sample empirical bayes moderated t-tests and the results seem to come out as expected (i.e. the most differentially expressed genes, bmp2 and dlx3, show up as the most differentially expressed). I have also tried performing paired t-tests on the data (paired since they share the same slide) after extracting the logR and logG values from the normalized M and A values, but I get very different results. Very few genes are differentially expressed with FDR control, and the top genes are no longer the bmp2 and dlx3 genes. Has anyone else tried doing paired t-tests on this data? The commands I used were: swirlnorm<-maNorm(swirl,norm="s") M<-maM(swirlnorm) A<-maA(swirlnorm) logG<-(2*A-M)/2 logR<-(2*A+M)/2 newswirl<-cbind(logR[,1], logG[,1], logR[,2], logG[,2], logR[,3], logG[,3], logR[,4], logG[,4]) classlabel<-c(1, 0, 0, 1, 1, 0, 0, 1) tstat<-mt.teststat(newswirl,classlabel,test="pairt", nonpara='"n") rawp<-2*(1-pt(abs(tstat),3)) result<-mt.rawp2adjp(rawp,proc=c("Bonferroni", "BH") resultp<-mt.reject(result$adjp,seq(0,1,0.05))$r resultp Rob.

I am a newcomer to DNA microarrays and I have recently been playing around with the swirl dataset that is available through the bioconductor R package. I have seen some results regarding the swirl data set on the internet that have used one-sample empirical bayes moderated t-tests and the results seem to come out as expected (i.e. the most differentially expressed genes, bmp2 and dlx3, show up as the most differentially expressed). I have also tried performing paired t-tests on the data (paired since they share the same slide) after extracting the logR and logG values from the normalized M and A values, but I get very different results. Very few genes are differentially expressed with FDR control, and the top genes are no longer the bmp2 and dlx3 genes. Has anyone else tried doing paired t-tests on this data? The commands I used were: swirlnorm<-maNorm(swirl,norm="s") M<-maM(swirlnorm) A<-maA(swirlnorm) logG<-(2*A-M)/2 logR<-(2*A+M)/2 newswirl<-cbind(logR[,1], logG[,1], logR[,2], logG[,2], logR[,3], logG[,3], logR[,4], logG[,4]) classlabel<-c(1, 0, 0, 1, 1, 0, 0, 1) tstat<-mt.teststat(newswirl,classlabel,test="pairt", nonpara='"n") rawp<-2*(1-pt(abs(tstat),3)) result<-mt.rawp2adjp(rawp,proc=c("Bonferroni", "BH") resultp<-mt.reject(result$adjp,seq(0,1,0.05))$r resultp Rob.