Jung‐Ying Tzeng

The paper introduces a Hi-C informed kernel association test to integrate 3D genome structure into variant-set association analysis for WGS data, showing improved detection of rare-variant sets.

This paper introduces a new framework for CNV association analysis in whole genome sequencing data, identifying additional CNVs linked to Alzheimer's Disease.

NIAGADS provides a national data repository for Alzheimer's Disease and related dementia genetics and genomics research, hosting genome and exome sequence data from over 209,000 samples.

This paper introduces a transfer learning framework with false negative control to improve polygenic risk prediction across heterogeneous datasets.

The paper identifies structural variations in whole-genome sequencing data from 16,905 ADSP subjects and finds associations with Alzheimer's disease and related endophenotypes.

CONCUR improves power in rare CNV analysis by comparing copy number profiles without requiring locus definitions.

The paper introduces POINT, a method that uses protein structure to identify individual rare variants associated with complex diseases by performing localized association tests.