limma: Help with time course experiment, common ref design
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@ntarisvoilafr-3895
Last seen 9.6 years ago
Dear all, I would like to analyze a time course experiment (5 time points, 2 technical replicates per time point) based on a common reference (=pool of all the conditions) design dataset with the limma package. By reading the contents of the limma user's guide, I found limma very interesting to first pre-process the data and then fit linear models. However, since I am not familiar with R, I face some issues with the linear models. Here is the script I'm have been using so far in order to normalize the data within and between arrays. library(limma) targets=readTargets("targets.txt") RG=read.maimages(files=c("1 R1.gpr","1 R2.gpr","4 R1.gpr","4 R2.gpr","11 R1.gpr","11 R2.gpr","15 R1.gpr","15 R2.gpr","18 R1.gpr","18 R2.gpr"), source="genepix") f=function(x) as.numeric(x$Flags > -50) RG=read.maimages(files=c("1 R1.gpr","1 R2.gpr","4 R1.gpr","4 R2.gpr","11 R1.gpr","11 R2.gpr","15 R1.gpr","15 R2.gpr","18 R1.gpr","18 R2.gpr"), source="genepix",wt.fun=f) MA=normalizeWithinArrays(RG, method="loess", bc.method="normexp", offset=50) MA.q=normalizeBetweenArrays(MA, method="quantile") Now with the linear models: I am a bit confused about the way to write the script. From the section 8.8 of the user's guide, I tried to see how to apply the example to mine but I can't get it anything worthy. targets<-readTargets("runxtargets.txt") targets SlideNumber Cy3 Cy5 1 1R1 ref 1R1 2 1R2 ref 1R2 3 4R1 ref 4R1 4 4R2 ref 4R2 5 11R1 ref 11R1 6 11R2 ref 11R2 7 15R1 ref 15R1 8 15R2 ref 15R2 9 18R1 ref 18R1 10 18R2 ref 18R2 design <- modelMatrix(targets,ref="ref") Found unique target names: 11R1 11R2 15R1 15R2 18R1 18R2 1R1 1R2 4R1 4R2 ref >From there, I don't know where I should go. My interest is to test a replicate effect as well as the time effect. Any help or suggestion would be greatly appreciated. In advance, sorry if the question sounds simplistic. Thanks. Nicolas ---------------------------------------------------------------------- Nicolas Taris Team 'Diversity and Connectivity in Coastal Marine Landscapes (DIV&CO)' UMR CNRS 7144 Station Biologique de Roscoff Place Georges Teissier France n.taris at voila.fr ---------------------------------------------------------------------- ____________________________________________________ Vous n?avez pas encore adress? vos voeux?? Retrouvez nos cartes sur http://carte-de-voeux.voila.fr
GO limma GO limma • 716 views
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