Screening properties of trend tests in genetic association studies

In genome-wide association study, extracting disease-associated genetic variants among millions of single nucleotide polymorphisms is of great importance. When the response is a binary variable, the Cochran-Armitage trend tests and associated MAX test are among the most widely used methods for association analysis. However, the theoretical guarantees for applying these methods to variable screening have not been built. To fill this gap, we propose screening procedures based on adjusted versions of these methods and prove their sure screening properties and ranking consistency properties. Extensive simulations are conducted to compare the performances of different screening procedures and demonstrate the robustness and efficiency of MAX test-based screening procedure. A case study on a dataset of type 1 diabetes further verifies their effectiveness.

Automated summary

In genome-wide association study, extracting disease-associated genetic variants is crucial but lacks theoretical guarantees for variable screening. We propose adjusted versions of Cochran-Armitage trend tests and MAX test for screening, proving their sure screening and ranking properties. Extensive simulations show the robustness and efficiency of MAX test-based screening. A case study on type 1 diabetes dataset further confirms their effectiveness.