Which would be the best way (a tool I suppose) to calculate the sample size in a case-control study in order to investigate the association of HLA alleles with a specific disease?
I am not sure I can use the G*Power analysis software for this type of study.
The problem is that we don't know, during study design, the HLA alleles that will be detected per HLA gene. For example we don't know if we will detect only HLA-A*01 and HLA-A*02 alleles within HLA-A gene or more.
I have found tools designed for sample size calculation in genetic association studies, such as the Genetic Power Calculator, QUANTO, ESPRESSO G etc. But I think that these tools are specific to genome association studies that want to associate the alleles and genotypes of specific SNPs with a disease.
Any idea on this issue?
Thank you!
For such a study, which is an HLA association study you need two cohorts. The first is the patient cohort (Cases) the second is the control cohort which needs to consist of a healthy random group of people from the same ethnic background as the patient group. The sample size depends on the expected effect and the number of comparisons. So it is difficult to say of hand how big the groups need to be.The minimal criteria is 50 patients versus 100 controls (1:2 ratio). If you have less of a chance that you will find any significant result will be very small, this will only be the case if the effect is very large. If you expect only a small difference you need a larger group.
In order to see if your control group is correct and does not contain subpopulations or family members you can check this by using the Hardy-Weinberg(HW) test. Pypop version 7 has such a test.To compare the HLA phenotype frequencies you can use the Woolf-Haldane Odds Ratio with a 95% confidence interval.To test the significance you can use the Fisher’s Exact test(2-tailed).You have to correct for multiple testing and for that, you can use the Sidak’s method or the Bonferroni's method. The correction can be done for the number of associations within a locus.
Hope this may help you.
Thank you.