[BioC] Affy normalization question

[Loren Engrav]

This is interesting, I guess after the fact in our case, but interesting

We did 3 Duroc and 3 Yorkshire pigs
Shallow and deep wound on each
And wounds biopsied at 1 2 3 12 and 20 weeks
So 60 samples obtained over 10 months, 6 samples at a time
And we pretty much processed them as we went, so rather then like 10 batches
of 6 each over 10 months
And then we normalized them all together

Should we have done something for batches? Did we miss something?

Thank you

-- 
Loren Engrav
Univ Washington
Seattle

> From: "James W. MacDonald" <jmacdon at med.umich.edu>
> Date: Sat, 22 Dec 2007 16:08:42 -0500
> To: <mwkimpel at gmail.com>
> Cc: Bioconductor_help <bioconductor at stat.math.ethz.ch>
> Subject: Re: [BioC] Affy normalization question
> 
> Hi Mark,
> 
> Mark W Kimpel wrote:
>> Not infrequently on this list the question arises as to how to perform
>> RMA on a large number of CEL files. The simple answer, of course, is to
>> use "justRMA" or buy more RAM.
>> 
>> As I have learned more about the wet-lab side of microarray experiments
>> it has come to my attention that there is a technical limitation in our
>> lab as to how many chips can actually be run at one time and that there
>> is a substantial batch effect between batches.
>> 
>> So, in my case at least, it seems to me that it would be incorrect to
>> normalize 60 CEL files at once when in fact they have been run in 4
>> batches of 16. Would it not be better to normalize them separately,
>> within-batch, and then include a batch effect in an analytical model?
> 
> Ideally you would randomize the samples when you are processing them (we
> randomize at four different steps) so you don't have batches that are
> processed together all the way through.
> 
> Whether or not you fit a batch effect in a linear model depends on how
> the samples were processed. If the lab processed all the same type of
> samples in each of the batches (please say they didn't), then any batch
> effect will be aliased with the sample types and fitting an effect won't
> really help.
> 
> If the batches were at least semi-randomized, then with 60 samples you
> won't be losing that many degrees of freedom, and it probably won't hurt
> to do so, and it just might help.
> 
>> 
>> Is my situation unique or, in fact, is this the way most MA wet-labs are
>> set up? If the latter is correct, should the recommendation not be to
>> use justRMA on 80 CEL files if they have been run in batches?
> 
> Regardless of how the lab is set up, once you get to large sample sets
> there will always be batches. If you do proper randomization of the
> samples during processing IMO there should be no need to do any
> post-processing adjustments for the batches.
> 
> Best,
> 
> Jim
> 
> 
>> 
>> Thanks,
>> Mark
> 
> -- 
> James W. MacDonald, M.S.
> Biostatistician
> Affymetrix and cDNA Microarray Core
> University of Michigan Cancer Center
> 1500 E. Medical Center Drive
> 7410 CCGC
> Ann Arbor MI 48109
> 734-647-5623
> 
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