Yan Zhang

Genetic and Cellular Architecture of Breast Cancer Risk Across Ancestries

This study analyzes breast cancer GWAS across multiple ancestries, finding similar heritability and genetic correlations, and identifies shared regulatory and cellular contexts.

A transition zone enriched WIF1⁺ basal cell subtype is associated with benign prostatic hyperplasia

The paper identifies a WIF1+ basal cell subtype enriched in the transition zone of the prostate and links it to benign prostatic hyperplasia through molecular and pathway analyses.

Immunometabolic Reprogramming by Thyroid-Stimulating Antibodies Drives Orbital Adipogenesis via Histone Lactylation in Thyroid Eye Disease

This paper identifies metabolic reprogramming driven by thyroid-stimulating antibodies as a key mechanism in thyroid eye disease, showing lactate promotes adipogenesis through histone lactylation.

Locally adaptive conformal prediction intervals for polygenic score-based phenotype prediction via residual normalization and data-driven stratification

This paper introduces C-SCNR, a framework for constructing calibrated prediction intervals for polygenic score-based phenotype prediction, outperforming existing methods in diverse error distributions and subgroups.

MACHINE: a robust and scalable multi-ancestry fine-mapping method using a continuous global-local shrinkage prior

MACHINE improves multi-ancestry fine-mapping by using a continuous prior and FDR control, identifying new causal variants in lipid traits and schizophrenia.

Modeling Post-Gastrula Development via Bidirectional Pluripotent Stem Cells

This study develops bidirectional pluripotent stem cells (BPSCs) capable of generating both trophoblast and epiblast lineages, enabling the recapitulation of post-gastrula development in vitro and in vivo.

A-TWAS: An aggregated transcriptome-wide association study model incorporating multiple Bayesian priors

A-TWAS improves transcriptome-wide association studies by integrating multiple Bayesian priors, enhancing predictive accuracy and identifying more disease-relevant genes.

A novel Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis

This paper introduces a Bayesian fine-mapping model, h2-D2, which outperforms existing methods in identifying causal variants and applies it to prostate cancer, discovering new variants and associated genes and pathways.

Grace-AKO: A Novel and Stable Knockoff Filter for Variable Selection Incorporating Gene Network Structures

Grace-AKO improves variable selection in high-dimensional genomic data by integrating gene network structures, achieving better finite-sample FDR control and model stability.

Metabolic control of histone acetylation for precise and timely regulation of minor ZGA in early mammalian embryos

This study identifies metabolic features in mouse pre-implantation embryos and shows that NAD+ synthesis is essential for development and regulates minor ZGA through H3K27ac erasure.

The GR2D2 Estimator for the Precision Matrices

The paper introduces the GR2D2 estimator for precision matrices, showing superior performance in high-dimensional sparse settings and identifying cancer pathways in RNA-seq data.

Multiethnic Polygenic Risk Prediction in Diverse Populations through Transfer Learning

This paper introduces TL-Multi, a transfer learning method to improve polygenic risk prediction in non-European populations using European GWAS data, achieving better accuracy than existing methods in SLE and asthma risk prediction.

Assessment of Polygenic Architecture and Risk Prediction based on Common Variants Across Fourteen Cancers

This study assesses polygenicity and risk prediction using common variants across 14 cancers, finding varying numbers of susceptibility variants and risk score effectiveness.

Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits and implications for the future

The paper estimates effect-size distributions of SNPs using GWAS summary statistics across 32 traits, revealing polygenic diversity and sample size requirements for heritability explanation.