Variational Inference

Quickdraws is a method that increases association power in quantitative and binary traits for GWAS without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference, and graphics processing unit acceleration. Published in Nature Genetics.

The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration.