[BioC] Influence of expression correlation on false positive ratio

[January Weiner]

Hi Jeff, many thanks.

> If the tests are only dependent in small groups, say because genes are
> grouped into small modules,  then most FDR methods in the p.adjust()
> function or the methods in the qvalue package will work.

Yes, but I wonder how it behaves in light of a more extensive
co-expression network (see for example the 2003 Stuart paper in
Science, http://www.sciencemag.org/content/302/5643/249.short). Has
anyone tried to simulate this? The co-expression modules, as have been
found in many papers, are sometimes anything but small.

> The Bonferroni
> correction controls a more conservative error rate, but also holds under
> dependence.

Sure, Bonferroni does not assume independence of the test, but it's
meager power means that many are not even considering this as an
option (I definitely use it when the test is strictly in hypothesis
testing mode and not further experiments are planned).

Best regards,
j.



>
> If the sources of dependence are more pervasive, like if there are batch
> effects:
>
> http://www.nature.com/nrg/journal/v11/n10/full/nrg2825.html
>
> Then you can either use the batch correction methods in Limma if, say, you
> know the date the samples were processed. Or, if you don't know the sources
> of large scale dependence, you can use the sva package:
>
> http://www.bioconductor.org/packages/devel/bioc/html/sva.html
>
> which implements the methods described here:
>
> http://www.pnas.org/content/early/2008/11/24/0808709105.abstract
>
>
> Best,
>
>
> Jeff
>
>
>
> On Jul 9, 2012 7:08 AM, "January Weiner"
> <january.weiner at mpiib-berlin.mpg.de> wrote:
>>
>> Hello,
>>
>> statistical methods for assessing significance of differences in
>> expression assume, correct me if I'm wrong, independence of the tests.
>> Does anyone have at hand any papers on the performance -- in terms of
>> type I error -- of methods such as limma / eBayes? I'm sure this issue
>> has been investigated in depth.
>>
>> Kind regards,
>>
>> January
>>
>> --
>> -------- Dr. January Weiner 3 --------------------------------------
>> Max Planck Institute for Infection Biology
>> Charitéplatz 1
>> D-10117 Berlin, Germany
>> Web   : www.mpiib-berlin.mpg.de
>> Tel     : +49-30-28460514
>> Fax    : +49-30-28450505
>>
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-- 
-------- Dr. January Weiner 3 --------------------------------------
Max Planck Institute for Infection Biology
Charitéplatz 1
D-10117 Berlin, Germany
Web   : www.mpiib-berlin.mpg.de
Tel     : +49-30-28460514
Fax    : +49-30-28450505