Hi.

I am having a few problems with LIMMA that never happened before. The  
first problem is trying to access and download my .gpr files into R.  
Previously I would change the working directory to a nominated file  
that contained all my .gpr files and other related bits. Here is the  
whole script that I have used in the past.


Could you please advise me why perhaps I cannot download my gpr files ?

controls<-read.table("blank and ratio.txt")
morecontrols<-read.table("utility and calib.txt")
morecontrols2<-read.table("neg.txt")
y<-as.vector(controls[,1])
z<-as.vector(morecontrols[,1])
z1<-as.vector(morecontrols2[,1])
xx<-c(z,y,z1)
files<-dir(pattern="*\\.gpr") ??? does not work for some reason
RG<-read.maimages(files,source="genepix")
RG$genes<-readGAL("mouse 22k gal annotated.gal")
RG$printer<-getLayout(RG$genes)
RGb<-backgroundCorrect(RG,method="none")
RG1<-filter.controls.to.NA(RGb,xx)
MA<-normalizeWithinArrays(RG1,RG$printer)
UVscale<-normalizeBetweenArrays(MA)
UVscaleBALB<-cbind(UVscale[,1],UVscale[,2]UVscale[,3]UVscale[,4] 
UVscale[,5]UVscale[,6])
UVscaleC57BL<-cbind(UVscale[,7],UVscale[,8],UVscale[,9],UVscale[, 
10],UVscale[,11],UVscale[,12)
BALBcA.UVscale <- UVscaleBALB$A
BALBcM.UVscale <- UVscaleBALB$M
C57BLA.UVscale <- UVscaleC57BL$A
C57BLM.UVscale <- UVscaleC57BL$M
BALBca<-is.na(BALBcM.UVscale)
BALBcb<-apply(BALBa,1,sum)
BALBczero<-which(BALBcb==0)
BALBcx.lmFit <- lmFit(BALBcM.UVscale[BALBczero,],c(1,-1,1,-1,1,1))
BALBcx.lmFit.Bayes <- eBayes(BALBcx.lmFit,proportion=0.10)
plot(BALBcx.lmFit.Bayes$coef,BALBcx.lmFit.Bayes$lods)
topTable(BALBcx.lmFit.Bayes,n=100)
RG$genes$ID[as.numeric(rownames(topTable(BALBcx.lmFit.Bayes,n=100)))]
M.UVscale[as.numeric(rownames(topTable(BALBcx.lmFit.Bayes,n=100)))]

MA$M[as.numeric(rownames(topTable(BALBcx.lmFit.Bayes,n=100)))] ???  
could this give me replicate M values in the toptable ranking order ?

C57BLa<-is.na(C57BLM.UVscale)
C57BLb<-apply(C57BL,1,sum)
C57BLzero<-which(C57BLb==0)
C57BLx.lmFit <- lmFit(C57BLM.UVscale[C57BLzero,],c(1,-1,1,-1,1,-1))
C57BLx.lmFit.Bayes <- eBayes(C57BLx.lmFit,proportion=0.10)
plot(C57BLx.lmFit.Bayes$coef,C57BLx.lmFit.Bayes$lods)
topTable(C57BLx.lmFit.Bayes,n=100)
RG$genes$ID[as.numeric(rownames(topTable(C57BLx.lmFit.Bayes,n=100)))]
M.UVscale[as.numeric(rownames(topTable(C57BLx.lmFit.Bayes,n=100)))]
MA$M[as.numeric(rownames(topTable(C57BLx.lmFit.Bayes,n=100)))]
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