We introduce GeneSIS, a statistical learning framework for modeling variant-level gene-by-sex interaction effects, and show it improves polygenic score prediction across 32 traits …
In this study, led by Xiaohe (Lucy) Tian, we showed that ancestry-aware integration of tissue-specific genomic annotations enhances the transferability of polygenic scores (PGS).
We introduce "hypometric genetics," an approach to investigate the genetic basis of binarized traits representing the presence of below-the-limit-of-quantification (BLQ) quality …
We developed GenoBoost, a polygenic score modeling approach, incorporating both additive and non-additive genetic dominance effects.
We developed a polygenic score training approach that allows direct inclusion of admixed individuals without the need for local ancestry inference and showed ancestry-diverse …
In this study led by Junyang Qian, we present a method to fit sparse multi-variate and multi-response regression model.
We performed a systematic assessment of the predictive performance of PRS models across >1,500 traits in UK Biobank and report 813 PRS models with significant predictive …
When applied to cardiometabolic biomarker traits in UK Biobank, MRP identified gene-biomarker associations that were not identified in single-variant GWAS analysis.
Using a set of GWAS summary statistics of diseases characterized from both European (UK Biobank and FinnGen) and East Asian (Biobank Japan) populations, we dissected latent DeGAs …
We analyzed the genetic basis of 35 blood and urine biomarkers in UK Biobank. We revealed that genetic effects on biomarkers inform the genetic basis of disease.
