Hi All, I would like to ask the forum if a paired t-test is better suited for my experimental design or a time course analysis. I have three time points T0, T6 and T12 for a group of animals. 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 used dual color arrays and hence separated the channels before fitting the model. For example when i try to do a paired t-test between T0 and T6 i get 50 warning messages. I have 5 different animals (biological replicates) that were given no treatment at T0 and a treatment at T6. I tried to run the code as given in limma manual for paired t-test. Since i have two color array i separated the channels first. However i do not understand where the code is wrong. Therefor can someone please explain if the code is right for performing a paired t-test and whether performing a t-test at all is a good idea or not for my design. > > 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 >> RG$genes<-readGAL() >> RG <- backgroundCorrect(RG, method="normexp", offset=50) > Green channel > Corrected array 1 > Corrected array 2 > Corrected array 3 > Corrected array 4 > Corrected array 5 > Red channel > Corrected array 1 > Corrected array 2 > Corrected array 3 > Corrected array 4 > Corrected array 5 >> MA.p <- normalizeWithinArrays(RG) >> MA.Aq<-normalizeBetweenArrays(MA.p,method="Aquantile") >> targets2<-targetsA2C(targets) >> targets2 > channel.col SlideNumber FileName Identity Pairing Target > 1.1 1 14117071 14117071.gpr 61 1 T6 > 1.2 2 14117071 14117071.gpr 61 1 T0 > 2.1 1 14117070 14117070.gpr 123 2 T6 > 2.2 2 14117070 14117070.gpr 123 2 T0 > 3.1 1 14116987 14116987.gpr 308 3 T6 > 3.2 2 14116987 14116987.gpr 308 3 T0 > 4.1 1 14117067 14117067.gpr 315 4 T0 > 4.2 2 14117067 14117067.gpr 315 4 T6 > 5.1 1 14117099 14117099.gpr 319 5 T0 > 5.2 2 14117099 14117099.gpr 319 5 T6 >> u<-unique(targets2$Target) >> Pairing<-factor(targets2$Pairing) >> Exposure<-factor(targets2$Target,levels=c("T0","T6")) >> design<-model.matrix(~Pairing+Exposure) >> corfit<-intraspotCorrelationMA.Aq,design) > There were 50 or more warnings (use warnings() to see the first 50) > Priyanka Kachroo Graduate Assistant Research Texas A&M University

Hi Priyanka, Since you put the two time points on the same array, you have explicitly set up the pairing already. You don't need to separate the data into a dual color analysis. Just read in normally, normalize within arrays (I don't know about between arrays - IIRC, Gordon doesn't seem to recommend that step for two-color arrays), and then make the comparison. You don't even have to create a design matrix - limma will automatically supply you with the correct design matrix for your experiment. As for paired t-test vs time course, it depends on what your hypothesis is. Best, Jim James W. MacDonald, M.S. Biostatistician Douglas Lab 5912 Buhl 1241 E. Catherine St. Ann Arbor MI 48109-5618 734-615-7826 >>> "Kachroo, Priyanka" 01/06/11 12:35 PM >>> Hi All, I would like to ask the forum if a paired t-test is better suited for my experimental design or a time course analysis. I have three time points T0, T6 and T12 for a group of animals. 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 used dual color arrays and hence separated the channels before fitting the model. For example when i try to do a paired t-test between T0 and T6 i get 50 warning messages. I have 5 different animals (biological replicates) that were given no treatment at T0 and a treatment at T6. I tried to run the code as given in limma manual for paired t-test. Since i have two color array i separated the channels first. However i do not understand where the code is wrong. Therefor can someone please explain if the code is right for performing a paired t-test and whether performing a t-test at all is a good idea or not for my design. > > 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 >> RG$genes<-readGAL() >> RG <- backgroundCorrect(RG, method="normexp", offset=50) > Green channel > Corrected array 1 > Corrected array 2 > Corrected array 3 > Corrected array 4 > Corrected array 5 > Red channel > Corrected array 1 > Corrected array 2 > Corrected array 3 > Corrected array 4 > Corrected array 5 >> MA.p <- normalizeWithinArrays(RG) >> MA.Aq<-normalizeBetweenArrays(MA.p,method="Aquantile") >> targets2<-targetsA2C(targets) >> targets2 > channel.col SlideNumber FileName Identity Pairing Target > 1.1 1 14117071 14117071.gpr 61 1 T6 > 1.2 2 14117071 14117071.gpr 61 1 T0 > 2.1 1 14117070 14117070.gpr 123 2 T6 > 2.2 2 14117070 14117070.gpr 123 2 T0 > 3.1 1 14116987 14116987.gpr 308 3 T6 > 3.2 2 14116987 14116987.gpr 308 3 T0 > 4.1 1 14117067 14117067.gpr 315 4 T0 > 4.2 2 14117067 14117067.gpr 315 4 T6 > 5.1 1 14117099 14117099.gpr 319 5 T0 > 5.2 2 14117099 14117099.gpr 319 5 T6 >> u<-unique(targets2$Target) >> Pairing<-factor(targets2$Pairing) >> Exposure<-factor(targets2$Target,levels=c("T0","T6")) >> design<-model.matrix(~Pairing+Exposure) >> corfit<-intraspotCorrelationMA.Aq,design) > There were 50 or more warnings (use warnings() to see the first 50) > Priyanka Kachroo Graduate Assistant Research Texas A&M University _______________________________________________ Bioconductor mailing list Bioconductor at r-project.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues