Geyu Zhou

Leveraging pleiotropy to improve genetic risk prediction across diseases

This paper improves genetic risk prediction across diseases by developing multi-trait polygenic scores that integrate GWAS data and show better performance than single-trait scores.

Joint Modeling of Effect Sizes for Two Correlated Traits: Characterizing Trait Properties to Enhance Polygenic Risk Prediction

This study introduces PleioSDPR, a method that improves polygenic risk prediction by jointly modeling genetic effects across correlated traits, showing significant accuracy gains in real trait applications.

Almost Free Enhancement of Multi-Population PRS: From Data-Fission to Pseudo-GWAS Subsampling

MIXPRS improves multi-population polygenic risk score prediction by integrating GWAS summary statistics without individual-level data, outperforming existing methods across multiple traits and populations.

JointPRS: A Data-Adaptive Framework for Multi-Population Genetic Risk Prediction Incorporating Genetic Correlation

JointPRS improves genetic risk prediction for non-European populations by integrating genetic correlation and multi-population data without individual-level tuning data.

A Bayesian Approach to Correcting the Attenuation Bias of Regression Using Polygenic Risk Score

This paper introduces a Bayesian method to correct attenuation bias in regression analysis using polygenic risk scores, showing improved coefficient estimation and credible interval coverage.

Evaluating and Improving Health Equity and Fairness of Polygenic Scores

This paper improves the portability and fairness of polygenic scores by introducing Joint-Lassosum, which outperforms existing methods in diverse ancestries.

OTTERS: A powerful TWAS framework leveraging summary-level reference data

OTTERS is a TWAS framework that uses summary-level eQTL reference data to estimate eQTL weights and perform omnibus TWAS, showing improved power and applicability.

Causal Haplotype Block Identification in Plant Genome-Wide Association Studies

This paper introduces HapFM, a haplotype-based fine-mapping framework for plant GWAS, which improves mapping power and resolution compared to existing methods.

A fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics

This paper introduces a Bayesian nonparametric method for predicting complex traits using summary statistics, showing it is adaptive, robust, and computationally efficient.

Leveraging functional annotation to identify genes associated with complex diseases

This paper introduces T-GEN, a method that improves gene-disease association identification by incorporating epigenetic annotations, resulting in more accurate and functionally relevant gene discoveries.