[R] (no subject)

[Anna Pluzhnikov]

Hi,
I need to run a Fisher's exact test on thousands of 2x2 contingency tables, and
repeat this process several thousand times (this is a part of the permutation
test for a genome-wide association study).

How can I run this process most efficiently? Is there any way to optimize R code?
 
I have my data in a 2x2xN array (N ~ 5 K; eventually N will be ~ 500 K), and use
apply inside the loop:
> for (iter in 1:1000) {
    apply(data,3,fisherPval)
  }
  fisherPval <- function(x) {
     fisher.test(x)$p.value
  }
Right now, it takes about 30 sec per iteration on an Intel Xeon 3.06GHz processor.

Thanks in advance. 

-- 
Anna Pluzhnikov, PhD
Section of Genetic Medicine
Department of Medicine
The University of Chicago






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