Monte Carlo permutation method for SNP multiple test correlation
MCPerm: A Monte Carlo permutation method for multiple test correlation in case-control association study Traditional permutation (TradPerm) test is an important non-parametric analysis method which can be treated as the gold standard for multiple testing corrections in case-control association study. However, it relies on the original single nucleotide polymorphism (SNP) genotypes and phenotypes data to perform a large number of random shuffles, and thus it is computationally intensive, especially for genome-wide association study (GWAS). To improve the calculation speed without changing the size of the TradPerm p-value, we developed a Monte Carlo permutation (MCPerm) method as an efficient alternative to TradPerm. Methods: MCPerm does not need to shuffle the original genotypes and phenotypes data. It uses Monte Carlo method, employs two-step hypergeometric distribution to generate the random number of genotypes (AA, Aa and aa) in cases and controls.