Hi, I work with dual channel technology and I would like to use limma for two way analysis. My experiment is as follow: FileName Cy3 Cy5 GL_251322310100_S02_.gpr WT3h NI3h GL_251322310101_S02_.gpr WT3h NI3h GL_251322310103_S02_.gpr Mut3h NI3h GL_251322310104_S02_.gpr Mut3h NI3h GL_251322310107_S02_.gpr WT18h NI3h GL_251322310136_S02_.gpr WT18h NI3h GL_251322310108_S02_.gpr Mut18h NI3h GL_251322310368_S02_.gpr Mut18h NI3h where I have two factors genotype: WT and Mut and Time: early and late and NI3h is the reference. Therefore it seems to be natural that my design matrix would be as WT3h Mut3h WT18h Mut18h GL_251322310100_S01 -1 0 0 0 GL_251322310101_S01 -1 0 0 0 GL_251322310103_S01 0 -1 0 0 GL_251322310104_S01 0 -1 0 0 GL_251322310107_S01 0 0 -1 0 GL_251322310136_S01 0 0 -1 0 GL_251322310108_S01 0 0 0 -1 GL_251322310368_S01 0 0 0 -1 then run fit<-lmFit(Marray,design) I want to answer the following questions: What is the effect of genotype on genes' expression? What is the effect of time on genes' expression? What is the synergistic effect of time and genotype? Since the most intuitive for me is to use the sum to zero parameterization method I created such contrast matrix Genotype.WTvsMut Time.EarlyvsLate Int WT3h 1 -1 1 Mut3h -1 -1 -1 WT18h 1 1 -1 Mut18h -1 1 1 then run contrasts<-contrasts.fit(fit,cotrasts.matrix) However from the example in chapter 14 in Limma users guide it seems that I had to run the my contrats matrix with lmFit function. I allowed myself to use the example in chapter 14 since reference design equivalent to affymetrix experiment after parametrizing it as mentioned above with my design matrix and fit it. So is it right the way I did it although in the example for factorial design my design of contrasts matrix is run with lmFit function? Is OK to run it without the intercept WT=c(1,1,1,1) if I'm not interesting in it? Thanks in advance, Ron

>>> "Gordon K Smyth" <smyth at="" wehi.edu.au=""> 10/06/05 12:45 PM >>> > Date: Thu, 06 Oct 2005 12:40:32 +0300 > From: "Ron Ophir" <ron.ophir at="" weizmann.ac.il=""> > Subject: [BioC] [limma] Factorial refernce design > To: "<bioconcutor" <bioconductor="" at="" stat.math.ethz.ch=""> > > Hi, > I work with dual channel technology and I would like to use limma for > two way analysis. My experiment is as follow: > FileName Cy3 Cy5 > GL_251322310100_S02_.gpr WT3h NI3h > GL_251322310101_S02_.gpr WT3h NI3h > GL_251322310103_S02_.gpr Mut3h NI3h > GL_251322310104_S02_.gpr Mut3h NI3h > GL_251322310107_S02_.gpr WT18h NI3h > GL_251322310136_S02_.gpr WT18h NI3h > GL_251322310108_S02_.gpr Mut18h NI3h > GL_251322310368_S02_.gpr Mut18h NI3h > where I have two factors genotype: WT and Mut and Time: early and late > and NI3h is the reference. > Therefore it seems to be natural that my design matrix would be as > WT3h Mut3h WT18h Mut18h > GL_251322310100_S01 -1 0 0 0 > GL_251322310101_S01 -1 0 0 0 > GL_251322310103_S01 0 -1 0 0 > GL_251322310104_S01 0 -1 0 0 > GL_251322310107_S01 0 0 -1 0 > GL_251322310136_S01 0 0 -1 0 > GL_251322310108_S01 0 0 0 -1 > GL_251322310368_S01 0 0 0 -1 > > then run fit<-lmFit(Marray,design) > > I want to answer the following questions: > What is the effect of genotype on genes' expression? > What is the effect of time on genes' expression? > What is the synergistic effect of time and genotype? > > Since the most intuitive for me is to use the sum to zero > parameterization method I created such contrast matrix > > Genotype.WTvsMut Time.EarlyvsLate Int > WT3h 1 -1 1 > Mut3h -1 -1 -1 > WT18h 1 1 -1 > Mut18h -1 1 1 > > then run contrasts<-contrasts.fit(fit,cotrasts.matrix) > > However from the example in chapter 14 in Limma users guide it seems > that I had to run the my contrats matrix with lmFit function. >I can't guess what you mean, or what difficulty you are imagining. The section on factorial >designs in the users guide is exactly equivalent to what you have given above. >Gordon Not exactly, in the user guide the contrasts.matrix as I described here is run by lmFit() whereas contrasts.fit() gets such matrix WT.SvsU Mu.SvsU Diff [1,] 0 0 0 [2,] 0 0 0 [3,] -2 -2 0 [4,] -2 2 4 to implement other questions. I guess that dealing with single channel experiment let run contrasts matrix directly in lmFit(). Ron > > > >> I allowed myself to use the example in chapter 14 since reference >> design equivalent to affymetrix experiment after parametrizing it as >> mentioned above with my design matrix and fit it. >> So is it right the way I did it although in the example for factorial >> design my design of contrasts matrix is run with lmFit function? >> Is OK to run it without the intercept WT=c(1,1,1,1) if I'm not >> interesting in it? >> >> Thanks in advance, >> Ron >

what do you mean by a contrasts matrix "run by lmFit"? I cannot guess what you can mean. There is no contrast argument to lmFit(). You do understand that the limma guide gives three different approaches to analysing the factorial design, and that your approach is equivalent to the first? This limma guide section is supposed to be pedagogic. You're not supposed to somehow mix all three approaches. Gordon On Thu, October 6, 2005 9:05 pm, Ron Ophir wrote: > > >>>> "Gordon K Smyth" <smyth at="" wehi.edu.au=""> 10/06/05 12:45 PM >>> > >> Date: Thu, 06 Oct 2005 12:40:32 +0300 >> From: "Ron Ophir" <ron.ophir at="" weizmann.ac.il=""> >> Subject: [BioC] [limma] Factorial refernce design >> To: "<bioconcutor" <bioconductor="" at="" stat.math.ethz.ch=""> >> >> Hi, >> I work with dual channel technology and I would like to use limma > for >> two way analysis. My experiment is as follow: >> FileName Cy3 Cy5 >> GL_251322310100_S02_.gpr WT3h NI3h >> GL_251322310101_S02_.gpr WT3h NI3h >> GL_251322310103_S02_.gpr Mut3h NI3h >> GL_251322310104_S02_.gpr Mut3h NI3h >> GL_251322310107_S02_.gpr WT18h NI3h >> GL_251322310136_S02_.gpr WT18h NI3h >> GL_251322310108_S02_.gpr Mut18h NI3h >> GL_251322310368_S02_.gpr Mut18h NI3h >> where I have two factors genotype: WT and Mut and Time: early and > late >> and NI3h is the reference. >> Therefore it seems to be natural that my design matrix would be as >> WT3h Mut3h WT18h Mut18h >> GL_251322310100_S01 -1 0 0 0 >> GL_251322310101_S01 -1 0 0 0 >> GL_251322310103_S01 0 -1 0 0 >> GL_251322310104_S01 0 -1 0 0 >> GL_251322310107_S01 0 0 -1 0 >> GL_251322310136_S01 0 0 -1 0 >> GL_251322310108_S01 0 0 0 -1 >> GL_251322310368_S01 0 0 0 -1 >> >> then run fit<-lmFit(Marray,design) >> >> I want to answer the following questions: >> What is the effect of genotype on genes' expression? >> What is the effect of time on genes' expression? >> What is the synergistic effect of time and genotype? >> >> Since the most intuitive for me is to use the sum to zero >> parameterization method I created such contrast matrix >> >> Genotype.WTvsMut Time.EarlyvsLate Int >> WT3h 1 -1 1 >> Mut3h -1 -1 -1 >> WT18h 1 1 -1 >> Mut18h -1 1 1 >> >> then run contrasts<-contrasts.fit(fit,cotrasts.matrix) >> >> However from the example in chapter 14 in Limma users guide it seems >> that I had to run the my contrats matrix with lmFit function. > >>I can't guess what you mean, or what difficulty you are imagining. > The section on factorial >>designs in the users guide is exactly equivalent to what you have > given above. > >>Gordon > > Not exactly, in the user guide the contrasts.matrix as I described here > is run by lmFit() whereas contrasts.fit() gets > such matrix > WT.SvsU Mu.SvsU Diff > [1,] 0 0 0 > [2,] 0 0 0 > [3,] -2 -2 0 > [4,] -2 2 4 > > to implement other questions. > > I guess that dealing with single channel experiment let run contrasts > matrix directly in lmFit(). > > Ron > > >> >> >> >>> I allowed myself to use the example in chapter 14 since reference >>> design equivalent to affymetrix experiment after parametrizing it > as >>> mentioned above with my design matrix and fit it. >>> So is it right the way I did it although in the example for > factorial >>> design my design of contrasts matrix is run with lmFit function? >>> Is OK to run it without the intercept WT=c(1,1,1,1) if I'm not >>> interesting in it? >>> >>> Thanks in advance, >>> Ron >> >