A scalable adaptive quadratic kernel method for interpretable epistasis analysis in complex traits.

Abstract excerpt

Our knowledge of the contribution of genetic interactions (epistasis) to variation in human complex traits remains limited, partly due to the lack of efficient, powerful, and interpretable algorithms to detect interactions. Recently proposed approaches for set-based association tests show promise in improving the power to detect epistasis by examining the aggregated effects of multiple variants. Nevertheless,...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Algorithms
• Share to Epistasis, Genetic
• Share to Genome-Wide Association Study