Hi All, I would like to ask the forum the best statistical analysis approach for my experimental design in which i have three time points T0, T6 and T12 for a treatment group. I need to evaluate the DE genes between T6&T0 and also T12&T0. Since the same set of animals were involved at all three time points, will a paired t-test for T6-T0 and T12-T0 be a better strategy or a time course analysis. I have dual color arrays hybridized in the following format. I tried to do a time series analysis by first separating the channels and then setting the contrasts as depicted in limma manual for single color arrays (section 8.8 in limma manual). However i get following error: "Error in intraspotCorrelationMA.Aq, design) : The number of rows of the design matrix should match the number of channel intensities, i.e., twice the number of arrays". Target file: SlideNumber FileName Cy3 Cy5 Identity 14117071 14117071.gpr T6 T0 61 14117070 14117070.gpr T6 T0 123 14116987 14116987.gpr T6 T0 308 14117067 14117067.gpr T0 T6 315 14117099 14117099.gpr T0 T6 319 14116988 14116988.gpr T0 T12 61 14116990 14116990.gpr T0 T12 123 14116964 14116964.gpr T0 T12 308 14116989 14116989.gpr T12 T0 315 14116948 14116948.gpr T12 T0 319 Here is code used so far: > targets<-readTargets("targets.txt") > RG<-read.maimages(targets,source="genepix",columns=list(R="F635 Median",G="F532 Median",Rb="B635",Gb="B532")) Read 14117071.gpr Read 14117070.gpr Read 14116987.gpr Read 14117067.gpr Read 14117099.gpr Read 14116988.gpr Read 14116990.gpr Read 14116964.gpr Read 14116989.gpr Read 14116948.gpr > RG$genes<-readGAL() > spottypes<-readSpotTypes("Spottypes.txt") > RG <- backgroundCorrect(RG, method="normexp", offset=50) Green channel Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 Corrected array 5 Corrected array 6 Corrected array 7 Corrected array 8 Corrected array 9 Corrected array 10 Red channel Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 Corrected array 5 Corrected array 6 Corrected array 7 Corrected array 8 Corrected array 9 Corrected array 10 > MA.p <- normalizeWithinArrays(RG) > MA.Aq<-normalizeBetweenArrays(MA.p,method="Aquantile") > targets2<-targetsA2C(targets) > targets2 channel.col SlideNumber FileName Identity Target 1.1 1 14117071 14117071.gpr 61 T6 1.2 2 14117071 14117071.gpr 61 T0 2.1 1 14117070 14117070.gpr 123 T6 2.2 2 14117070 14117070.gpr 123 T0 3.1 1 14116987 14116987.gpr 308 T6 3.2 2 14116987 14116987.gpr 308 T0 4.1 1 14117067 14117067.gpr 315 T0 4.2 2 14117067 14117067.gpr 315 T6 5.1 1 14117099 14117099.gpr 319 T0 5.2 2 14117099 14117099.gpr 319 T6 6.1 1 14116988 14116988.gpr 61 T0 6.2 2 14116988 14116988.gpr 61 T12 7.1 1 14116990 14116990.gpr 123 T0 7.2 2 14116990 14116990.gpr 123 T12 8.1 1 14116964 14116964.gpr 308 T0 8.2 2 14116964 14116964.gpr 308 T12 9.1 1 14116989 14116989.gpr 315 T12 9.2 2 14116989 14116989.gpr 315 T0 10.1 1 14116948 14116948.gpr 319 T12 10.2 2 14116948 14116948.gpr 319 T0 > lev<-c("T0","T6","T12") > u<-unique(targets2$Target) > f<-factor(targets2$Target,levels=lev) > design<-model.matrix(~0+f) > colnames(design)<-lev > corfit<-intraspotCorrelationMA.Aq,design) Error in intraspotCorrelationMA.Aq, design) : The number of rows of the design matrix should match the number of channel intensities, i.e., twice the number of arrays > Can someone please help me with this error and how to obtain differentially expressed genes for contrasts "T6-T0" and "T12-T0". Regards Priyanka Kachroo