Hi all,

I am trying to compare the SNPs from a "target gene" to the SNPs of genes from the rest of the cohort (say about 100 individuals, 50 genes) to determine if there is a deviation from Hardy-Weinberg Equilibrium. The issue I am having is that the SNPs vary in CC/CG/GG, AC,AA,CC, TA,AA,TT, etc. which is making it hard for me to come up with a contingency table for X2 or exact testing.

My first intuition is to first exclude genes that do not have the same SNPs as the target gene (e.g. AA,AC,CC) and create a contingency table which compares the frequency of certain SNPs to the rest of the cohort along the lines of:

           Target Gene  |    Rest of the Cohort
AA           12         |         65
AC           19         |         104
CC           32         |         55

And then preform Chi Squared test for p-value. I believe a significant p-value (>0.05) means that HWE is rejected as the null hypothesis is that the population is in the HWE.

I really have no other ideas on how to do this, and am not really sure if this would be right. All my other ideas for analysis feel like garbage.

Edit: My reasoning behind this is I am comparing the genotype frequencies to see if there is a major difference. Source: https://en.wikipedia.org/wiki/Hardy%E2%80%93Weinberg_principle