I have 3 data frames for three groups of patients and in each of them I have the number of mutation types like insertion, deletion, SNP and total of mutations for each patients. In each group I have different number of patients like below
> head(dat1)
patient DEL INS SNP total
1: LP6008337-DNA_H06 927 773 40756 42456
2: LP6008334-DNA_D02 1049 799 31009 32857
> dim(dat1)
[1] 21 6
>
head(dat2)
Patient DEL INS SNP total
1: LP6008031-DNA_E01 13552 3374 62105 79031
2: LP6005500-DNA_G01 539 500 43451 44490
> dim(dat2)
[1] 33 6
>
> head(dat3)
Patient DEL INS SNP total
1: LP6005935-DNA_F03 39168 16739 58095 114002
2: LP6008269-DNA_D08 849 910 103501 105271
> dim(dat3)
[1] 106 6
I want to show if the number of each mutational category and total is different between these three groups by chi-square test
Actual question is if total number of mutations, SNP, DEL and INS are statistically significant among groups. I used pairwise t test but I afraid this test is not a suitable test for the distribution of data moreover I don't know how to visualize the p-value
Imagining the comparison of total number of mutations between three groups, this picture is a good example
Or in this plot they compare several features but only two groups
Can you help ?
Thanks