# Does multiple pairwise fisher exact test need multiple testing correction?

I am aware of that multiple testing correction is needed when multiple hypothesis tests are simultaneously performed. However, I am a little confused by the word "simultaneously".

Say I have hundereds of samples and I derived multiple features (variables) from each sample. With this sample-feature matrix, I would like to perform pairwise fisher exact test for feature co-occurrence. Do I need to carry out multiple testing correction on the P-value of each paired feature?

I guess multiple testing correction is needed. However, I can consider that each of the pairwise fisher exact test was carried out individually and each raw p-value represents the significance of correponding paired features, right?

If you are going to look at lots of relationships separately and then claim you have discovered something when $$p\leq 0.05$$, then this is a multiplicity issue (i.e. if you only do enough tests you will appear to "discover" something). This has almost nothing to do with what your analysis method is (except that some hierarchical models might be said to have some multiplicity protection "build-in").
In fact, with hundreds of comparisons made, you will need to do something to be taken seriously with any claim based on $$p\leq 0.05$$. Whether the something is to control the familywise type I error rate, or say control the false discovery rate, or something else is to some extent up to you (but straying too far from the conventions of your field may not be a good idea).