Optimizing and benchmarking polygenic risk scores with GWAS summary statistics
Our method is a powerful and general modeling technique that can continue to combine the best-performing PRS methods out there through ensemble learning and could become an integral component for all future PRS applications.
Authors
- Yuchang Wu (ORCID: https://orcid.org/0000-0002-6985-3998)
- Yixuan Wu (ORCID: https://orcid.org/0000-0001-5443-9746)
- Jiacheng Miao (ORCID: https://orcid.org/0000-0002-4524-7408)
- Zhongxuan Sun (ORCID: https://orcid.org/0009-0004-5682-2078)
- Zijie Zhao (ORCID: https://orcid.org/0000-0001-6502-5821)
- Jie Song (ORCID: https://orcid.org/0000-0003-4799-3575)
- Qiongshi Lu (ORCID: https://orcid.org/0000-0002-4514-0969)
- Tim Gruenloh
- Meiyi Yan
Institutions
- University of Wisconsin–Madison (US)
- Oklahoma State University Center for Health Sciences (US)
Publication Details
- Journal
- Genome biology
- Published
- 2024-10-08
- DOI
- https://doi.org/10.1186/s13059-024-03400-w
- Citations
- 19
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 9.91