[BioC] a question about LIMMA

[Gordon K Smyth]

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
>