Hi all

I am trying to utilise Limma to analyses data from a two colour
environmental microarray in an experiment that is investigating
microbial function under contrasting vegetation types. 

After loading the data and performing background subtraction and
normalisation, I have attempted to correct for spot-specific dye effects
by including a "dye factor" in the design matrix.  My code is as
follows:

> #create design that included dye factor aswell as vegetation types ...
> #
> design.sc<-model.matrix(~0+factor(targets2$Target)+factor(targets2
$channel.col))
> colnames(design.sc)<-c("veg.3","veg.4","veg.2","veg.1","Dye")
> design.sc
   veg.3 veg.4 veg.2 veg.1 Dye
1       0       0   0     1   0
2       0       0   1     0   1
3       0       0   1     0   0
4       0       1   0     0   1
5       0       1   0     0   0
6       1       0   0     0   1
7       1       0   0     0   0
8       0       0   0     1   1
9       0       0   0     1   0
10      0       1   0     0   1
11      0       1   0     0   0
12      0       0   0     1   1
13      0       0   1     0   0
14      1       0   0     0   1
15      1       0   0     0   0
16      0       0   1     0   1
attr(,"assign")
[1] 1 1 1 1 2
attr(,"contrasts")
attr(,"contrasts")$`factor(targets2$Target)`
[1] "contr.treatment"

attr(,"contrasts")$`factor(targets2$channel.col)`
[1] "contr.treatment"

> # next do intraspot correlation ...
> library(limma)
> corfit<-intraspotCorrelation(MA,design.sc)
Loading required package: statmod
Warning messages:
1: In remlscore(y, X, Z) : reml: Max iterations exceeded
2: In remlscore(y, X, Z) : reml: Max iterations exceeded
3: In remlscore(y, X, Z) : reml: Max iterations exceeded
4: In remlscore(y, X, Z) : reml: Max iterations exceeded
5: In remlscore(y, X, Z) : reml: Max iterations exceeded
6: In remlscore(y, X, Z) : reml: Max iterations exceeded
7: In remlscore(y, X, Z) : reml: Max iterations exceeded
8: In remlscore(y, X, Z) : reml: Max iterations exceeded
9: In remlscore(y, X, Z) : reml: Max iterations exceeded
> fit<-lmscFit(MA,design.sc,correlation=corfit$consensus)
> fit <- eBayes(fit)
> #make contrasts ...
> cont.matrix1 <- makeContrasts("veg.1-veg.2",levels=design.sc)
> fit2.1 <- contrasts.fit(fit, cont.matrix1)
> cont.matrix2 <- makeContrasts("veg.1-veg.3",levels=design.sc)
> fit2.2 <- contrasts.fit(fit, cont.matrix2)
> cont.matrix3 <- makeContrasts("veg.1-veg.4",levels=design.sc)
> fit2.3 <- contrasts.fit(fit, cont.matrix3)
> fit2.1<-eBayes(fit2.1)
> fit2.2<-eBayes(fit2.2)
> fit2.3<-eBayes(fit2.3)

This is all a bit new for me, can someone please confirm if I have
correctly addressed any spot*dye effects with this code. 

Many thanks in advance for your help.

Regards

Ross

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