I have mutational catalogues of 4 samples like below
> head(out) Responders1 Nonresponders1 Responders2 Nonresponders2 A[C>A]A 11744 13546 2897 3655 A[C>A]C 5144 7172 2295 2163 A[C>A]G 939 1257 290 279 A[C>A]T 6065 7997 2078 2088 C[C>A]A 8969 11155 2055 2582 C[C>A]C 4050 6657 1367 1173 > > dim(mut)  96 4 >
Note: A[C>A]A - Single nucleotide base substitution
I want to look if mutational substitutions are different between samples
I have tried
wilcox.test(mut$Responders2,mut$Nonresponders2) t.test(mut$Responders2,mut$Nonresponders2) var.test(mut$Responders2,mut$Nonresponders2) fisher.test(mut$Responders2,mut$Nonresponders2,simulate.p.value=TRUE) kruskal.test(mut$Responders2,mut$Nonresponders2)
To find a difference but I think you may know a better test to find any difference here
This is base shift (mutation, substitution across genome of each patient). I guess mutations happen randomly but I don't know if mutational caller algorithm also pick them by randomness. I expect the shift of A (Adenine) to C (Cytosine) in a group of these patients be higher than the other group. This higher rate likely should be due to some background than randomness picked by algorithm. So I think null hypothesis is that rate of base shifting is not the same in both group. I also don't expect a normalised distribution of base shifting rather a poison distribution.
Can you help please?