Ping Zeng

SpatialESD improves spatial domain detection in spatial transcriptomics by integrating multiple methods and capturing both direct and indirect relationships between clusters.

The paper evaluates genetic architecture similarity and diversity between East Asian and European populations for 37 traits using summary statistics, finding shared genetic overlap but also population-specific effects.

This paper uses Mendelian randomization and mediation analysis to evaluate the causal effects of blood lipid levels on gout using summary-level GWAS data, finding that HDL and TG influence gout risk through serum urate.

This paper introduces PMR-Egger, a probabilistic Mendelian randomization method to test and control horizontal pleiotropy in transcriptome-wide association studies, showing improved type I error control and power.

This study finds an inverse association between low birth weight and chronic kidney disease in observational studies but no causal link using Mendelian randomization.

This study uses genetic methods to assess if higher BMI causes amyotrophic lateral sclerosis, finding no causal link.

This paper introduces JMAP, a model averaging method for genetic risk prediction that integrates pathway information, showing improved accuracy over existing methods in simulations and real cancer datasets.

This paper introduces iMAP, a method for pleiotropic association mapping in GWASs that improves power by integrating SNP annotations and using a penalized Gaussian mixture model.

This paper introduces a method to identify trait-relevant tissues using GWAS summary statistics and omics annotations, improving tissue inference and constructing more powerful association tests.

This paper introduces a non-parametric polygenic method, DPR, for genetic prediction of complex traits and evaluates its performance across multiple applications.

The paper introduces MAPIT, a method to detect epistasis by testing marginal epistatic effects instead of direct pairwise interactions, improving computational efficiency and statistical power.