Hui Tang

This paper introduces an improved linear mixed model for multivariate genome-wide association studies that handles incomplete data and reduces computational complexity.

The paper introduces a rapid mixed model for genome-wide epistatic association analysis that handles multiple polygenic effects and demonstrates its efficiency on yeast and human datasets.