Zhuozheng Shi

The paper uses admixture mapping in the All of Us Research Program to identify genetic ancestry associations with 22 traits, finding 71 novel loci where African ancestry explains phenotypic variation.

FELIX improves genetic association analysis by accounting for local ancestry in admixed populations, increasing significant loci and improving polygenic score prediction.

This study evaluates the GIRA approach in a health system, finding 30.4% of patients labeled high-risk based on genomic data, with ancestry differences and social deprivation influences.

CalPred provides well-calibrated prediction intervals for polygenic risk scores, maintaining calibration across different contextual factors unlike other methods.

The paper shows that statistical uncertainty explains disagreement in type 2 diabetes polygenic scores and proposes using uncertainty measures to improve risk prediction.

This study identifies genetic loci associated with Meniere's disease and links them to inner ear development and retinoic acid metabolism.

This paper examines how genetic interactions with ancestry affect polygenic scores and shows that models of local and global ancestry interactions can be distinguished using partial polygenic scores when causal variants are known.

The paper improves polygenic prediction accuracy by using diverse datasets, showing greater benefits for underrepresented populations.

The paper introduces context-aware prediction intervals for polygenic scores to improve calibration across diverse populations and traits.