[BioC] Array Set - Multiple Testing Problem
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Fri Sep 11 17:56:21 CEST 2009
On Sep 11, 2009, at 11:44 AM, Sean Davis wrote:
> On Fri, Sep 11, 2009 at 11:20 AM, Sean Davis <seandavi at gmail.com>
>> On Fri, Sep 11, 2009 at 9:47 AM, Tefina Paloma <tefina.paloma at gmail.com
>>> To be able to fit the same model to all arrays, an additional
>>> normalization would be necessary, so to make all the arrays really
>>> and I don't want to over-normalize the data either.....
>>> therefore I just thought of an sensible p value adjustment
>> You can adjust the entire list of p-values from all lists, if you
>> like, as
>> an alternative. However, assuming that the arrays are of the same
>> technology, the probe-level variances should be similar, so you
>> could also
>> combine the normalized data. I'm not sure what "model" you mean,
>> as each
>> test is done within a probe and, therefore, would not cross
>> arrays. But I
>> may have misunderstood what you are trying to do.
> I made a further assumption above, which I should probably make
> While the array technology is important in determing the variance, the
> biologic behavior of the probes on the array contributes, also.
Sorry if this is too noob-ish of a question, but I'm curious about
your choice of words. Could you explain this point a bit further? It
sounds like you are referring to the actual probes that are
synthesized onto the array, no?
What biologic behavior do you expect these probes to have? Are you
referring to them forming some secondary structure or something? If
so, why would one expect some explicitly differing behavior between
the same probes on different arrays (assuming no array impurities and
the arrays were performed using the same protocol, or whatever).
Just curious, thanks ...
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
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