I'm looking to test for set enrichment and I'm wondering whether a fisher's exact test or hypergeometric test is more appropriate (and, if there isn't a straightforward answer, what the relative merits are).
To lay out an example problem, I have a set of 400 objects, 150 of which belong to class A. I draw 50 objects, and there is an overlap of 15.
I could lay this out as a matrix (15, 50-15, 150-15, and 400 – 50 – 150 + 15) and use this matrix to calculate a fisher's exact test. Alternately, I could use the hypergeometric distribution in R and do phyper(15, 150, 400-150, 50).
Is one of these preferably to the other and, if so, why? Thanks!
Best Answer
Hypergeometric test assesses the extremeness of observing x or more of "good" cases (overlap) and thus same as a one-sided Fisher's exact test (where the alternative hypothesis is "greater" in R jargon). If you do not care about the directionality then you can use two-sided Fisher's exact test.