A simulation study of permutation, bootstrap, and gene dropping for assessing statistical significance in the case of unequal relatedness.

We used simulations to evaluate methods for assessing statistical significance in association studies. When the statistical model appropriately accounted for relatedness among individuals, unrestricted permutation tests and a few other simulation-based methods effectively controlled type I error rates; otherwise, only gene dropping controlled type I error but at the expense of statistical power.