[BioC] Batch effect in limma

[Yuan Hao]

Dear list,

I got 12 Affymetrix arrays for 4 RNA samples, 3 replicates(from 3  
batches individually) for each sample. I want to look at the  
differential expression between these samples. While after clustering,  
we found obvious batch effect within the data, so we decided to add  
the batch effect into the linear model. I set up the design matrix as  
followings, but we can't find any differentially expressed gene that  
were expected, so would someone help me to have a look whether there  
is any problem with my design and contrast matrix? Thank you very much  
in advance:

Array	Sample	Batch
1		-/-		3
2		+/+		3
3		-/+		1
4		+/+		1
5		-/+		3
6		+/-		3
7		-/-		1
8		+/-		1
9		-/-		2
10		+/-		2
11		+/+		2
12		-/+		2

 > S <- c("-/-","+/+","-/+","+/+","-/ 
+","+/-","-/-","+/-","-/-","+/-","+/+","-/+")
 > S <- factor(S, level = c("+/+","-/+","+/-","-/-"))
 > B <- c(3,3,1,1,3,3,1,1,2,2,2,2)
 > B <- factor(B, level = c(1,2,3))
 > design <- model.matrix(~0+S+B)
 > colnames(design)<- 
c("sample1","sample2","sample3","sample4","Batch3","Batch2")
 > design

  sample1 sample2 sample3 sample4 Batch3 Batch2

1        0       0       0       1      1      0

2        1       0       0       0      1      0

3        0       1       0       0      0      0

4        1       0       0       0      0      0

5        0       1       0       0      1      0

6        0       0       1       0      1      0

7        0       0       0       1      0      0

8        0       0       1       0      0      0

9        0       0       0       1      0      1

10       0       0       1       0      0      1

11       1       0       0       0      0      1

12       0       1       0       0      0      1

attr(,"assign")

[1] 1 1 1 1 2 2

attr(,"contrasts")

attr(,"contrasts")$TS

[1] "contr.treatment"



attr(,"contrasts")$BE

[1] "contr.treatment"

 > fit<-lmFit(eset.gcrma,design)

 > contrast.matrix<-makeContrasts(a=sample1-sample2,b=sample1- 
sample3,c=sample2-sample4,levels=design)

 > contrast.matrix

         Contrasts

Levels     a  b  c

  sample1  1  1  0

  sample2 -1  0  1

  sample3  0 -1  0

  sample4  0  0 -1

  Batch3   0  0  0

  Batch2   0  0  0

 > fit2<-contrasts.fit(fit,contrast.matrix)

 > fit2<-eBayes(fit2)


Cheers,
Yuan