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Fine-tuning Polygenic Risk Scores with GWAS Summary Statistics
Zijie Zhao, Yanyao Yi, Yuchang Wu, Xiaoyuan Zhong, Yupei Lin, Timothy J. Hohman, Jason Fletcher, View ORCID ProfileQiongshi Lu
doi: https://doi.org/10.1101/810713
Zijie Zhao
1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI
Yanyao Yi
2Department of Statistics, University of Wisconsin-Madison, WI
3Eli Lilly and Company, Indianapolis, IN
Yuchang Wu
1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI
Xiaoyuan Zhong
4University of Wisconsin-Madison, Madison, WI
Yupei Lin
4University of Wisconsin-Madison, Madison, WI
Timothy J. Hohman
5Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN
6Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
Jason Fletcher
7La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI
8Department of Sociology, University of Wisconsin-Madison, Madison, WI
9Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI
Qiongshi Lu
1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI
2Department of Statistics, University of Wisconsin-Madison, WI
9Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI
Posted October 18, 2019.
Fine-tuning Polygenic Risk Scores with GWAS Summary Statistics
Zijie Zhao, Yanyao Yi, Yuchang Wu, Xiaoyuan Zhong, Yupei Lin, Timothy J. Hohman, Jason Fletcher, Qiongshi Lu
bioRxiv 810713; doi: https://doi.org/10.1101/810713
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