Lai Jiang

Fine-Mapping and Credible Set Construction using a Multipopulation Joint Analysis of Marginal Summary Statistics from Genome-wide Association Studies

This paper introduces mJAM, a multi-population fine-mapping method that improves credible set construction by incorporating population-specific LD structures and demonstrates its effectiveness in real GWAS data.

A Hierarchical Approach Using Marginal Summary Statistics for Multiple Intermediates in a Mendelian Randomization or Transcriptome Analysis

This paper introduces hJAM, a hierarchical model that improves causal inference in Mendelian randomization and transcriptome-wide association studies by incorporating prior information and accounting for SNP correlations.