Jiayi Qu

This paper introduces SBayesAPP, a Bayesian model that estimates annotation-stratified pleiotropy and co-polygenicity between complex traits using GWAS summary statistics, revealing cell-type-specific genetic correlations.

This study integrates longitudinal metabolite profiles into genomic prediction models for pig traits, showing improved prediction accuracy depending on the trait and timepoint of metabolite sampling.

The paper introduces MegaBayesianAlphabet, a Bayesian regression framework for genome-wide prediction and association studies, showing improved accuracy in genetic value prediction and marker discovery using high-dimensional phenotypic data.

MegaLMM improves genetic value prediction accuracy by analyzing thousands of traits simultaneously in genomic studies.

The paper derives an exact distribution of linkage disequilibrium (LD) over generations in a finite population, accounting for mutation, selection, and minor allele frequency filtering.