How to statistically/bioinformatically measure the contribution of mutations to - (May/24/2020 )

Dear All, 

I am stuck with one analyses. I have the frequency of occurence of several gene mutations in 50 bacterial isolates and these isolates were either resistant or senstive to certain drug. So the outcome is two phenotypes (resistant and senstive bacterial to certain drug).

I am searching for a statistical/bioinformatics analyses that could give a numerical estimate for the "importance" of each of these mutations in causing particular phenotype. In other words, how can one rank the mutations according to their contribution to inducing resistance to certain antimicrobial ? 

Example: I have the frequency of occurence of mutations A, B, C, D in 50 bacterial isolates (as 1: present, 01:L absent) and some of these isolates are resistant or senstive to certain drug. Which analyses is best for this estimate ? 

Thanks 

Principal component analysis? Depends on what sort of stats you have on each one - this is way beyond my understanding of stats, so you might want to talk to a proper statistician if you can.