mixed models analysis with limma
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@gordon-smyth
Last seen 3 hours ago
WEHI, Melbourne, Australia
Dear Christian, See Section 8.2 of the limma User's Guide. The 'block' argument of duplicateCorrelation() and lmFit() handles random effects. Best wishes Gordon > Date: Fri, 25 Sep 2009 08:33:43 +0200 > From: Christian Bri?re <briere at="" scsv.ups-tlse.fr=""> > Subject: [BioC] mixed models analysis with limma > To: bioconductor at stat.math.ethz.ch > Content-Type: text/plain > > Hello, > > I would like to know whether it is possible to analyze microarray data > from a mixed model experiment with Limma package. > I have 4 independent experiments (random effect) and 3 treatments (fixed > effect), and 1 microarray (monocolor) for each combination of the two > factors. > > Thank you for your help > -- > > Christian Bri?re > UMR CNRS-UPS 5546 > BP42617 Auzeville > F-31326 Castanet-Tolosan (France) > tel: +33(0)5 62 19 35 90 > Fax: +33(0)5 62 19 35 02 > E-mail: briere at scsv.ups-tlse.fr <mailto:briere at="" scsv.ups-="" tlse.fr=""> > > http://www.scsv.ups-tlse.fr > http://www.gdr2688.ups-tlse.fr <http: www.gdr2688.ups-="" tlse.fr="" index.php=""> > http://www.ifr40.cnrs.fr
Microarray limma Microarray limma • 2.8k views
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@christian-briere-3259
Last seen 10.2 years ago
Dear Gordon, Thank you for your help. This exactly what I need I think. May I ask you some more help ? I would like to know whether the script below is correct : There are 4 biological experiments : F, H, O and CB and there is 1 treatment with three levels: T , C and CL I'd like to know genes that are differentially expressed between "C" and "T", and between "CL" and "C": > # > # Normalized data are in Dnorm > exp<-c("F","F","F","H","H","H","H","O","O","O","CB","CB","CB","CB") > corfit<-duplicateCorrelation(Dnorm, block=exp) > corfit$consensus [1] -0.07705255 > tr<-c("T","C","CL","T","C","CL","T","C","CL","T","C","CL") > tr<-factor(tr, levels=c("T","C","CL")) > design<-model.matrix(~tr) > fit<-lmFit(Dnorm,design, block=exp, cor=corfit$consensus) > fit<-eBayes(fit) > # comparison between treatment C and T > ttC<-topTable(fit, coef="trC", p.value=0.01, n=Inf) > dim(ttC2) [1] 8834 7 > # comparison between treatment CL and C > cont.matrix<-cbind("CLvsC"=c(0,1,-1)) > fitCCL<-contrasts.fit(fit2, cont.matrix) > fitCCL<-eBayes(fitCCL) > ttCCL<-topTable(fitCCL, coef=1, p.value=0.01, n="Inf") > dim(ttCCL) [1] 8798 7 > Thank you for your help Christian Gordon K Smyth a écrit : > Dear Christian, > > See Section 8.2 of the limma User's Guide. The 'block' argument of > duplicateCorrelation() and lmFit() handles random effects. > > Best wishes > Gordon > >> Date: Fri, 25 Sep 2009 08:33:43 +0200 >> From: Christian Bri?re <briere@scsv.ups-tlse.fr> >> Subject: [BioC] mixed models analysis with limma >> To: bioconductor@stat.math.ethz.ch >> Content-Type: text/plain >> >> Hello, >> >> I would like to know whether it is possible to analyze microarray data >> from a mixed model experiment with Limma package. >> I have 4 independent experiments (random effect) and 3 treatments (fixed >> effect), and 1 microarray (monocolor) for each combination of the two >> factors. >> >> Thank you for your help >> -- >> >> Christian Bri?re >> UMR CNRS-UPS 5546 >> BP42617 Auzeville >> F-31326 Castanet-Tolosan (France) >> tel: +33(0)5 62 19 35 90 >> Fax: +33(0)5 62 19 35 02 >> E-mail: briere@scsv.ups-tlse.fr <mailto:briere@scsv.ups-tlse.fr> >> >> http://www.scsv.ups-tlse.fr >> http://www.gdr2688.ups-tlse.fr >> <http: www.gdr2688.ups-tlse.fr="" index.php=""> >> http://www.ifr40.cnrs.fr -- Christian Brière UMR CNRS-UPS 5546 BP42617 Auzeville F-31326 Castanet-Tolosan (France) tel: +33(0)5 62 19 35 90 Fax: +33(0)5 62 19 35 02 E-mail: briere@scsv.ups-tlse.fr <mailto:briere@scsv.ups-tlse.fr> http://www.scsv.ups-tlse.fr http://www.gdr2688.ups-tlse.fr <http: www.gdr2688.ups-="" tlse.fr="" index.php=""> http://www.ifr40.cnrs.fr [[alternative HTML version deleted]]
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You have to specify the design matrix to duplicateCorrelation(). Gordon On Mon, 28 Sep 2009, Christian Bri?re wrote: > Dear Gordon, > Thank you for your help. This exactly what I need I think. > May I ask you some more help ? I would like to know whether the script below > is correct : > > There are 4 biological experiments : F, H, O and CB > and there is 1 treatment with three levels: T , C and CL > > I'd like to know genes that are differentially expressed between "C" and "T", > and between "CL" and "C": > >> # >> # Normalized data are in Dnorm >> exp<-c("F","F","F","H","H","H","H","O","O","O","CB","CB","CB","CB") >> corfit<-duplicateCorrelation(Dnorm, block=exp) >> corfit$consensus > [1] -0.07705255 >> tr<-c("T","C","CL","T","C","CL","T","C","CL","T","C","CL") >> tr<-factor(tr, levels=c("T","C","CL")) >> design<-model.matrix(~tr) >> fit<-lmFit(Dnorm,design, block=exp, cor=corfit$consensus) >> fit<-eBayes(fit) >> # comparison between treatment C and T >> ttC<-topTable(fit, coef="trC", p.value=0.01, n=Inf) >> dim(ttC2) > [1] 8834 7 >> # comparison between treatment CL and C >> cont.matrix<-cbind("CLvsC"=c(0,1,-1)) >> fitCCL<-contrasts.fit(fit2, cont.matrix) >> fitCCL<-eBayes(fitCCL) >> ttCCL<-topTable(fitCCL, coef=1, p.value=0.01, n="Inf") >> dim(ttCCL) > [1] 8798 7 >> > > Thank you for your help > Christian > > Gordon K Smyth a ?crit : >> Dear Christian, >> >> See Section 8.2 of the limma User's Guide. The 'block' argument of >> duplicateCorrelation() and lmFit() handles random effects. >> >> Best wishes >> Gordon >> >>> Date: Fri, 25 Sep 2009 08:33:43 +0200 >>> From: Christian Bri?re <briere at="" scsv.ups-tlse.fr=""> >>> Subject: [BioC] mixed models analysis with limma >>> To: bioconductor at stat.math.ethz.ch >>> Content-Type: text/plain >>> >>> Hello, >>> >>> I would like to know whether it is possible to analyze microarray data >>> from a mixed model experiment with Limma package. >>> I have 4 independent experiments (random effect) and 3 treatments (fixed >>> effect), and 1 microarray (monocolor) for each combination of the two >>> factors. >>> >>> Thank you for your help >>> -- >>> >>> Christian Bri?re >>> UMR CNRS-UPS 5546 >>> BP42617 Auzeville >>> F-31326 Castanet-Tolosan (France) >>> tel: +33(0)5 62 19 35 90 >>> Fax: +33(0)5 62 19 35 02 >>> E-mail: briere at scsv.ups-tlse.fr <mailto:briere at="" scsv.ups-="" tlse.fr=""> >>> >>> http://www.scsv.ups-tlse.fr >>> http://www.gdr2688.ups-tlse.fr <http: www.gdr2688.ups-="" tlse.fr="" index.php=""> >>> http://www.ifr40.cnrs.fr > > > -- > > Christian Bri?re > UMR CNRS-UPS 5546 > BP42617 Auzeville > F-31326 Castanet-Tolosan (France) > tel: +33(0)5 62 19 35 90 > Fax: +33(0)5 62 19 35 02 > E-mail: briere at scsv.ups-tlse.fr <mailto:briere at="" scsv.ups-="" tlse.fr=""> > > http://www.scsv.ups-tlse.fr > http://www.gdr2688.ups-tlse.fr <http: www.gdr2688.ups-="" tlse.fr="" index.php=""> > http://www.ifr40.cnrs.fr > > > >
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