On Jan 3, 2008 12:31 PM, Alex Tsoi <tsoi.teen@gmail.com> wrote:

> Dear all,
>
> I am currently doing a meta analysis of microarray data. I first gather
> few
> groups of data from GEO that have their raw .CEL data, and then I found
> out
> that one group of data does not have the .CEL as raw data, but instead it
> has the TXT format data (the TXT format, they call it the Series Matrix
> files in GEO).
>
> I am just wondering if anyone know how could I do the analysis on this
> type
> of data (please point me to the right function or package). The original
> plan I had is to use justGCRMA() to background corrected and normalized
> all
> the data, then do the analysis on each group of the data, and compare each
> of the group result. However, I am kind of facing this difficulty as this
> .TXT data could not be converted back to the .CEL format, and I have to
> think of a standard way to treat (normalize, background corrected) all the
> groups equally.....
>

Hi, Alex.  The GSE files typically contain summarized, normalized data (and
the GSM records will typically describe that data handling protocol,
whatever it was).  Therefore, you will probably not be able to process these
using the typical affy tools.

You can use GEOquery to get the data into R.  Just do:

gse <- getGEO('GSEXXXXX', GSEMatrix=TRUE)

As for meta-analysis, I'm not sure that simply using justGCRMA on all the
data from various sites done at different times is necessarily the best way
to go.  You will need to look at the specifics of the various data sets that
you have downloaded with regard to your hypotheses to see if such a
meta-analysis will be expected to produce valid results.  If you have
questions, you can ask in more detail here, of course.

Sean

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