[BioC] Possible to combine U133A&B Affy chip in one analysis?

[James W. MacDonald]

Hi Zaki,

On 10/1/2012 5:15 AM, Zaki Fadlullah wrote:
> Hello gentle people,
>
> As the topic suggests, would it be possible to combine data of U133A&B affy chip? and more importantly how...
>
> The main objective is to find differently expressed genes, and to maximise the use of available data...as there are many papers I have read that conducted experiments on U133A&U133B chips (on the same sample set), however in their result/discussion sections the papers seems to show only one figure
>
> In this particular paper that I am trying to understand how they found differently expressed genes from these two separate chips, they have a sample set (with 2 replicates each) on U133A and the same sample set (also with 2 replicates each) on U133B.
>
> I would like to maximise the available data in from all chips and conduct the analysis. I am familiar on how to differently expressed each one separately using R (limma, affy), but would it be possible to combine expression value of these two chips??

If you are doing simple univariate analyses (e.g., modeling your data 
one probeset at a time), then there isn't really that much to be gained 
by combining. You could argue that you will get a better empirical Bayes 
estimate of variability, but doubling the number of probesets from 12k 
to 24k won't IMO really improve things.

I may be missing something, but right now I can't come up with a 
compelling reason to combine the chips (but am happy to be corrected 
;-D). I would just do the analyses separately by chip, and then if you 
want to combine results at the end, you can simply rbind() the output.

Best,

Jim


>
>
> I am assuming I would have to normalise them separately, but after that I am not quite sure what to do or if it is even possible..
>
> Any help/ suggestions would be greatly appreciated
>
> Many thanks
> Zack
>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
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Seattle WA 98105-6099