I have a table of 288 rows and 4 columns where each row corresponds to a tumour sample, and each column is a gene. All of the values are 0 or 1, to indicate whether there's a mutation in a particular gene for a particular sample, but obviously each sample can have more than one mutation.
I want to test for correlations between pairs of columns, to see if mutations in certain genes are likely to appear in the same sample or if they're likely to not appear in the same sample (the null hypothesis being that they're occur independently). Normally for categorical data I'd use Fisher's exact test, but it seems like all the examples I see use mutually exclusive variables, which is not the case for my dataset.
What would be the most relevant test for this kind of dataset?