Hi Gordon,
I just used the single channel analysis for a loop design.  I am 
wondering if it is possible that there is a code error that swaps the 
roles of Cy3 and Cy5.  The results did not
make sense when I fitted with as shown below.

Cy5=c("S ","SB ","F ","St ","MB ","C ","P ","L ","C ",
"MB ","St ","F ","SB ","S ","L ","P ")
Cy3=c("MB ","C ","P ","L ","St ","S ","SB ","F ",
"St","F ","P ","C ","MB ","L","SB","S")
targets=data.frame(RG$targets,Cy3=Cy3,Cy5=Cy5)
TargetArray=targetsA2C(targets)

  MAb <- normalizeBetweenArrays(MA,method="Aq")

design <- model.matrix(~Target,data=TargetArray)
corfit <- intraspotCorrelation(MAb,design)
fit <- lmscFit(MAb,design,correlation=corfit$consensus)
cont.matrix <- rbind(rep(0,7),diag(1,7))
fit2 <- contrasts.fit(fit,cont.matrix)


But when I used
targets=data.frame(RG$targets,Cy3=Cy5,Cy5=Cy3)

the results make sense (we know what several of the genes do and they 
show up in the right place this way) and the estimated error variance 
is cut in half. I can tediously go through and compute the some of 
the tissue means by hand to compare with the lmscFit output, but I 
thought you would know where in the code to check this.

Thanks,


Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111

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