Yunfeng Ruan

This paper develops a polygenic score for peripheral artery disease (PAD) that improves risk prediction across diverse populations and identifies high-risk individuals for adverse limb events.

Cross-trait Elastic Net mixing of PGS Catalog scores (PRSmix+) lifted mean PRS accuracy 1.72-fold in Europeans and 1.42-fold in South Asians over the best single score.

Admix-kit provides tools for genetic analysis of admixed populations, enabling simulation, association testing, and polygenic scoring.

The paper identifies IL1RAP and AIM2 as key modifiers of CHIP-associated cardiovascular risk using UK Biobank data and CRISPR experiments in mice.

This paper introduces PRS-CSx, a method that improves polygenic prediction across ancestrally diverse populations by integrating GWAS summary statistics and sharing genetic effects.

The paper identifies genomic variants regulating junction-skipping using RNA-seq and GWAS data to understand their role in complex diseases.