Xia Shen

The paper extends a genomic prediction method to include marker interaction effects, showing small improvements in predictions using Arabidopsis thaliana data.

This paper identifies epistatic genetic interactions underlying root length variation in Arabidopsis thaliana, revealing that epistasis cancels additive genetic variance, and discovers functional candidate genes.

The paper introduces a genetic architecture score inspired by the Gini index to quantify the complexity of genetic architecture in quantitative traits and validates its effectiveness through simulations.

The paper calculates exact p-values for genome-wide association studies in inbred populations, showing improved detection power and reduced inflation compared to standard methods.

The paper identifies CMT2 genetic variation linked to methylation changes and temperature adaptation in Arabidopsis thaliana using a novel genome-wide association method.