[BioC] limma - Considering Batch Effect
James MacDonald
jmacdon at med.umich.edu
Tue Aug 7 19:47:06 CEST 2007
Hi Nathan,
Nathan Haigh wrote:
> I know this topic has arisen a few times from searching the mail
> archive, but I'm still not clear on what/how to do this.
>
> Here is my experimental setup:
> Array Param1 Param2 Rep Batch
> 1 H 4 1 1
> 2 H 4 2 2
> 3 H 4 3 2
> 4 H 20 1 1
> 5 H 20 2 2
> 6 H 20 3 2
> 7 H 37 1 1
> 8 H 37 2 2
> 9 H 37 3 2
> 10 L 4 1 1
> 11 L 4 2 2
> 12 L 4 3 2
> 13 L 20 1 1
> 14 L 20 2 2
> 15 L 20 3 2
> 16 L 37 1 1
> 17 L 37 2 2
> 18 L 37 3 2
>
> All rep 1's were processed in batch 1 and reps 2 and 3 were processes in
> batch 2. From using GeneSpring, and conducting a cluster analysis on
> experimental parameters, there is a clear batch effect. In GeneSpring, I
> normalised the arrays, such that gene1 from array1 was divided by the
> median of gene1 over arrays from batch1. Likewise, gene1 from array2 was
> divided by the median of gene1 across arrays in batch2. These
> successfully removed the batch effect. I'd like to be able to remove the
> batch effect doing something similar, or accounting for it in limma.
>
> In essence, I want to remove the variability in the reps caused by the
> batch effect.
>
> Could anyone explain how this can/should be done?
Sure. Just add the Batch effect to your design matrix. For instance, if
you want to model the differences in Param1, you would do something like:
> design <- model.matrix(~0+factor(rep(1:2,
each=9))+factor(rep(rep(1:2,1:2),6)))
> colnames(design) <- c("H","L","Batch")
> design
H L Batch
1 1 0 0
2 1 0 1
3 1 0 1
4 1 0 0
5 1 0 1
6 1 0 1
7 1 0 0
8 1 0 1
9 1 0 1
10 0 1 0
11 0 1 1
12 0 1 1
13 0 1 0
14 0 1 1
15 0 1 1
16 0 1 0
17 0 1 1
18 0 1 1
attr(,"assign")
[1] 1 1 2
attr(,"contrasts")
attr(,"contrasts")$`factor(rep(1:2, each = 9))`
[1] "contr.treatment"
attr(,"contrasts")$`factor(rep(rep(1:2, 1:2), 6))`
[1] "contr.treatment"
Then you can do the contrast between H and L.
Best,
Jim
> Thanks
> Nathan
>
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--
James W. MacDonald, MS
Biostatistician
UMCCC cDNA and Affymetrix Core
University of Michigan
1500 E Medical Center Drive
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