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I would like to compute co-occurence and mutual exclusivity for a set of events divided in two groups (A and B). Each event E_{x,y} represents if a mutation occurs in the gene x from sample y These two groups of events are encoded in two matrix (A and B) with the same number of columns and rows ( columns = samples ; rows = genes). Cell values can either by 1 (mutation occurs) or 0 (no mutation occurs). A_{x,y} represent an event of type A for gene x from sample y. B_{k,l} represents an event of type B for gene k and l.

I would like to test co-occurence or mutual exclusivity for each pair of genes. Thus comparing each pair of A_{i,.} ; B_{i,.} where i is 1..number of genes.

Is a fisher exact test a good option ?

Thank you

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Yes, Fisher exact test seems a reasonable option to me. For each gene you have a 2x2 table with for numbers of occurences (A and B, A and not B, not A and B, not A and not B). The odds ratio (together with the p-value) will tell you whether you have co-occurences or mutual exclusivity.

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  • $\begingroup$ Ok thank you. And is fisher test ok if there is might be a causality effect between events from group A to B. So to check if event A_{x,.} is = 1 is there some event B more prone to be 1 ( or 0 ) $\endgroup$ – Nicolas Rosewick Mar 10 at 8:52
  • $\begingroup$ No, the the Fisher test does not tell you anything about causality. It can be that A causes B, that B causes A or that another cause C causes both A and B. $\endgroup$ – citronrose Mar 11 at 11:27
  • $\begingroup$ ok thank you. Reading a little bit about testing causality and indeed it's not trivial .. $\endgroup$ – Nicolas Rosewick Mar 11 at 12:04

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