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Fisher's exact test for comparing TCR clonotype counts

I am trying to apply Fisher's exact test in R for a matrix which contains count data for a TCR-seq dataset. Each row in the matrix is a different tcr clonotype and each column represents different conditions. The cells have normalized counts (to account for sequencing depth differences) for each tcr for each condition. I want to apply fisher's exact test to test each tcr against rest of the tcr to test null hypothesis that they are not different between conditions.

I am looking for a solution similar to the following line of code that iterates over the full matrix and provides me with a p-value.

apply(tab, 1, function(x) fisher.test(matrix(x,nrow=2,ncol=2))$p.value)

How do I set this up in R?Any suggestions are welcome.

This approach was applied in the following paper. However, since I am not a statistician, I couldn't apply the notations to my script very well.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4442358/

This is similar to the question that has been asked below (but in the context of gene expression).

https://stats.stackexchange.com/questions/201586/fishers-exact-test-in-rna-seq?newreg=6c8ab398c53c425ebc2f7e380a3cb15c

Thanks.

r tcr-seq

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