Association tests through combining p-values for case control genome-wide association studies

To detect single nucleotide polymorphisms (SNPs) that are associated with a common disease in a case control genome-wide association study (GWAS), powerful yet robust tests are desirable. Current available robust approaches in this area are mainly based on the optimal trend tests for some specific genetic models, such as recessive, additive, multiplicative, and dominant models. In this paper, we propose a class of robust association tests through combining p-values obtained by partitioning the 2 by 3 contingency table of the SNP data. Through simulation study and application to real data, we show that the proposed tests are powerful and robust. They provide alternative association tests for GWAS.