[BioC] paired samples test in limma package

[Yi, Ming (NIH/NCI) [C]]

Hi, List:

I have a question regarding paired samples test in limma package.

Here is what I got

####W and B are race
####T and N are tumor and normal(paired by same Samples), respectively
####Samples are individual patients: tar$AccNum########
#### 

> library(limma);
> tar<-readTargets("Test_Desc.txt");
> mydata<-read.delim("TestData.txt",as.is=TRUE,row.names=1);
> mydata<-mydata[,tar$mRNASampleNames];
> tar$Type<-gsub("Tumor","T",tar$Type)
> tar$Type<-gsub("Normal","N",tar$Type)
> group1<-paste(tar$RACE,tar$Type,sep=".");
> group<-factor(group1, levels=c( "W.T","W.N","B.T","B.N"))
> Samples<-factor(tar$AccNum);

####first option to set up the design matrix#########
> design<-model.matrix(~Samples+group);
> colnames(design)<-sub("group","",colnames(design));
> colnames(design)<-sub("Samples","",colnames(design));
> colnames(design)[1] <- "Intercept";
> con.matrix<-makeContrasts(AA.T_AA.N=B.T-B.N,EA.T_EA.N=-W.N,levels=design);
> lmFit(mydata,design)->fit1;
Coefficients not estimable: B.N 
Warning message:
Partial NA coefficients for 26804 probe(s) 
> contrasts.fit(fit1, con.matrix)->fit2
Error in contrasts.fit(fit1, con.matrix) : 
  trying to take contrast of non-estimable coefficient
################it did not work!!! not sure why??#########


##########then I tried the 2nd option to set up the design matrix####

> design<-model.matrix(~-1+group+Samples);
> colnames(design)<-sub("group","",colnames(design));
> colnames(design)<-sub("Samples","",colnames(design));
> con.matrix<-makeContrasts(AA.T_AA.N=B.T-B.N,EA.T_EA.N=W.T-W.N,levels=design);
> lmFit(mydata,design)->fit1;
Coefficients not estimable: S14810 
Warning message:
Partial NA coefficients for 26804 probe(s) 
> contrasts.fit(fit1, con.matrix)->fit2
> eBayes(fit2)->fit3
>

#######it works somehow in terms of generating lists, but leave an warning message when I did the fit1 using > lmFit(mydata,design)->fit1 (...Coefficients not estimable: S14810) I am sure why is like this? Using some other dataset, I didn't see such warning at all. It seems dataset specific, I am not sure why there is warning here and whether the list come out is good or not.


Could someone please have some suggestions?

Thanks in advance!

Myi