We develop methods to analyze whole exome and whole genome sequencing data,
including de novo variants and rare variants, to identify genes for both
congenital and developmental diseases as well as complex diseases.
 Y. Xie, W. Jiang, W. Dong, H. Li, S. C. Jin, M. Brueckner, H. Zhao (2022)Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease. PLOS Genetics, 18: e1010252.
 H. Guo, L. Hou, Y. Shi, S. C. Jin, X. Zeng, B. Li, R. P. Lifton, M. Brueckner, H. Zhao, Q. Lu (2022) Quantifying concordant genetic effects of de novo mutations on multiple disorder. eLife, 11: e75551.
 Y. Xie, M. Li, W. Dong, W. Jiang, H. Zhao (2021) M-DATA: A statistical approach to jointly analyzing De Novo mutations for multiple traits. PLOS Genetics, 17: e1009849.
 M. Li, X. Zeng, C. Jin, S. C. Jin, W. Dong, M. Brueckner, R. Lifton, Q. Lu, H. Zhao (2021) Integrative modeling of transmitted and de novo variants identifies novel risk genes for congenital heart disease. Quantitative Biology, 9: 216-227.
© 2022 Hongyu Zhao, Ph.D.
Created by Eddie, Chen and Wangjie.