CODEWITHSUNDEEP
rmemoryworkspace
nak3c
nak3c

Reputation: 439

how to avoid R fisher.test workspace errors

I am preforming a fisher's exact test on a large number of contingency tables and saving the p-val for a bioinformatics problem. Some of these contingency tables are large so I've increased the workspace as much as I can; but when I run the following code I get an error:

result <- fisher.test(data,workspace=2e9)
LDSTP is too small for this problem. Try increasing the size of the workspace.

if I increase the size of the workspace I get another error:

result <- fisher.test(data,workspace=2e10)
cannot allocate memory block of size 134217728Tb

Now I could just simulate pvals:

result <- fisher.test(data, simulate.p.value = TRUE, B = 1e5)

but Im afraid Ill need a huge number of simulations to get accurate results since my pvals may be extremely small in some cases.

Thus my question whether there is some way to preemptively check if a contingency table is too complex to calculate exactly? In those cases alone I could switch to using a large number of simulations with B=1e10 or something. Or at least just skip those tables with a value of "NA" so that my job actually finishes?

Upvotes: 3

Views: 4948

Answers (1)

Łukasz Deryło
Łukasz Deryło

Reputation: 1860

Maybe you colud use tryCatch to get desired behaviour when fisher.test fails? Something like this maybe:

tryCatchFisher<-function(...){
    tryCatch(fisher.test(...)$p.value,
    error = function(e) {'too big'})
    }

Upvotes: 3

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