Hi terdon,

Take a look at ?p.adjust and its argument n.  For example, you could adjust
B pv values by using

p.adjust(pv[1:B], method = 'BH', n = B)

Then, you can continue processing other subsets of pv and concatenate the
result.  Here, a for() loop might be useful.

HTH,
Jorge


On Tue, Mar 8, 2011 at 8:49 AM, terdon <> wrote:

> Hello all,
>      I am calculating probabilities of association for terms in the
> GeneOntology database. I have ~4e7 probabilities and I would like to
> correct
> for multiple testing. At the moment I have something like the following:
>
> pv is a vector containing my 4e7 probabilities.
>
> To run the multiple testing corrections I do:
>
> mt <- mt.rawp2adjp(pv, proc="BH")
>
> Because of the size of the vector this takes a VERY long time and a LOT of
> memory. I cannot split the job into smaller ones since all values in the
> vector are required for the calculation.
>
> Can anyone think of a trick that would allow me to reduce the memory usage
> of this procedure? Or t least make it faster?
>
> Thanks
>
> --
> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
>
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