[BioC] a question about LIMMA

[Francois Pepin]

Dear Erika,

Are you talking about the whole genome 44k (or 4x44k) arrays?

In our situation (with the arrays mentioned above), we have found those 
replicate probes to behave in a virtually identical manner, to the point 
where we arbitrarily select one of the probes and simply ignore the rest.

As Gordon was saying, you can simply average the values. We have found 
this not to be necessary, but it would definitely not hurt.

I do not know of any package to use them for quality control. If you see 
one replicate that is really different from the others, you would likely 
worry about the array.

Francois

Gordon K Smyth wrote:
> Dear Erika,
> 
> limma doesn't explicitly handle irregular replicates.  (In my lab, we 
> haven't had to work with any of the new generation of Agilent arrays 
> yet, so haven't had to solve the issues with them.)
> 
> Your best bet may be to simply average over the replicates for each 
> probe, after normalisation, and before using lmFit().  This is not hard, 
> but requires some programming in R.
> 
> Best wishes
> Gordon
> 
> On Tue, 3 Jun 2008, Erika Melissari wrote:
> 
>> Dear Dr Smyth,
>>
>> I am a PhD student at University of Pisa. I frequently use LIMMA 
>> package to handle gene expression microarray data. I have a question 
>> about spot copies management by LIMMA. I know that LIMMA needs all 
>> spots on the array are in the same number of copy ( e.g. each spot in 
>> double ). In my research group It is just starting a project in wich 
>> we use Agilent microarrays (so high density microarrays) and on these 
>> arrays there is only a block of probes, positioned in a random 
>> fashion, in more than one spot for each probe. Moreover there is not 
>> the same number of copies for each probe in this block. Then we have 
>> not regularly spaced replicate spots on the same array. Please, check 
>> the gal file by human Agilent microarrays sent as Email attachment, in 
>> which I highlighted in red some spots (but not all...) to better 
>> explain to you this situation. Is LIMMA able to manage this situation? 
>> That is, is LIMMA able to use this kind of random replicated spots to 
>> perform a quality control procedure, to fit the linear model and to 
>> produce a unique fold change value for this probe? Can I use any kind 
>> of strategy to solve this problem? Does It exists a free package that 
>> does this?
>>
>> Thank you very much for any information about this topic.
>>
>> Best Regards
>>
>> Erika Melissari
>>
> 
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