Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy

Yung Chun Wang, Yuchang Wu, Julie Choi, Garrett Allington, Shujuan Zhao, Mariam Khanfar, Kuangying Yang, Po Ying Fu, Max Wrubel, Xiaobing Yu, Kedous Y. Mekbib, Jack Ocken, Hannah Smith, John Shohfi, Kristopher T. Kahle, Qiongshi Lu, Sheng Chih Jin

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.

Original languageEnglish
Article number175
JournalJournal of Personalized Medicine
Issue number2
StatePublished - Feb 2022


  • Bioinformatics
  • Common variant
  • Gene therapy
  • Genomics
  • Precision medicine
  • Rare variant
  • Statistical genetics


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