[BioC] Converting data into MAlist to use in LIMMA

[Aubin-Horth Nadia]

Stephen, Sean and Jose

Thanks for your help. Using a simple numerical matrix that contains my  
M ratios for each array works perfectly in LIMMA. I will work on  
building an MAlist to keep the info on each probe with the stats  
output to make htings simpler in the long run.

Thank you very much for your help

Nadia

On Feb 10, 2010, at 1:41 PM, stephen sefick wrote:

> The convert package is a bioconductor package and I think the function
> that you want is
>
> as(foo, "MAlist")
>
> On Wed, Feb 10, 2010 at 12:40 PM, Aubin-Horth Nadia
> <Nadia.Aubin-Horth at bio.ulaval.ca> wrote:
>> HI everybody
>>
>> We conducted a two-color microarray experiment using a 19 000-probe  
>> home
>> made cDNA array. Our experiment contains 12 arrays. We use LIMMA to  
>> do all
>> the normalization and model fitting and stats. Out of the 19 000  
>> probes,
>> several clones are part of the same contig, as annotated by TIGR.  
>> We decided
>> to average the M values for these clones that correspond to a  
>> single contig
>> to obtain a single M value for a given contig, for each array  
>> separately. We
>> also wanted to remove probes that were called empty after  
>> sequencing (but
>> they were already on the printed microarray). We exported the MAlist
>> containing the normalised data (called "MAptip.nba.scale") and  
>> extracted the
>> M data for each of the 12 slides in Python. We did the averaging and
>> removing of "empty" spots and now have a new file with columns  
>> containing
>> information on block, row, column, spot ID, annotation information  
>> for the
>> contigs (and singletons) and then data for each slide in the  
>> following
>> columns. Each row contains the averaged M values.
>>
>> We looked for a way to convert this file back into a MAlist so we can
>> specify our design and do a fit. We read in the archives about a  
>> library
>> called convert (which we did not find on CRAN) and info on how to  
>> transform
>> data into an exprSet for affy data. Would someone be willing to  
>> help us with
>> this task and give us pointers?
>>
>> Thank you very much
>>
>> Nadia Aubin-Horth
>> Assistant professor
>> Biology Department
>> Institute of Integrative and Systems Biology
>> Université Laval
>> Québec, Canada
>>
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>
>
>
> -- 
> Stephen Sefick
>
> Let's not spend our time and resources thinking about things that are
> so little or so large that all they really do for us is puff us up and
> make us feel like gods.  We are mammals, and have not exhausted the
> annoying little problems of being mammals.
>
> 								-K. Mullis