Xiang Zhu

SuSiNE improves genetic fine-mapping by incorporating signed functional priors and multi-basin ensembling to better resolve LD ambiguity and uncertainty.

RETROFIT deconvolves cell-type mixtures in spatial transcriptomics without requiring references, outperforming existing methods and matching reference-based approaches when references are imperfect.

The paper identifies sequence-conserved enhancer-like elements across tissues and links them to complex traits using GWAS data, finding tissue-specific heritability and novel candidate genes for BMI and schizophrenia.

The paper develops a method to detect complex structural variants across human genomes and finds they are associated with phenotypic hotspots and evolutionary changes.

This study identifies 118 candidate causal genes and 21 novel lipid loci on the X chromosome through a multi-ancestry meta-analysis of blood lipid levels, revealing sex-biased effects and pleiotropy with cardiovascular and hormonal traits.

This study conducts a trans-ancestry GWAS using chronic ALT elevation as a proxy for NAFLD, identifies 77 significant loci, and validates 17 SNPs with histology and imaging data, revealing genetic links to metabolic and inflammatory traits.

This study identifies genetic regulators of DNA replication timing in human pluripotent stem cells, revealing a histone code and combinatorial regulatory mechanisms.

This paper develops a Bayesian framework integrating GWAS with regulatory networks to improve the identification of trait-associated genes by modeling network topology.

Multi-ethnic type 2 diabetes (T2D) meta-analysis of 228,499 cases and 1,178,783 controls finds 318 previously unreported loci, 804 expression-colocalized genes, and 13 SNP-by-T2D vascular-outcome interactions.

The paper introduces a new enrichment analysis method using GWAS summary statistics to identify trait-associated genes, pathways, and tissues across 31 human phenotypes, uncovering previously unreported associations.

This paper introduces a Bayesian framework for large-scale multiple regression using GWAS summary statistics, enabling heritability estimation and association detection without individual-level data.