Optimizing and benchmarking polygenic risk scores with GWAS summary statistics

Zijie Zhao; Tim Gruenloh; Yixuan Wu; Zhongxuan Sun; Jiacheng Miao; Yuchang Wu; Jie Song; Qiongshi Lu

doi:10.1101/2022.10.26.513833

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Optimizing and benchmarking polygenic risk scores with GWAS summary statistics

View ORCID ProfileZijie Zhao, Tim Gruenloh, Yixuan Wu, Zhongxuan Sun, View ORCID ProfileJiacheng Miao, Yuchang Wu, Jie Song, View ORCID ProfileQiongshi Lu

doi: https://doi.org/10.1101/2022.10.26.513833

Zijie Zhao

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

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Tim Gruenloh

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

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Yixuan Wu

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

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Zhongxuan Sun

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

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Jiacheng Miao

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

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Yuchang Wu

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

2Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI

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Jie Song

3Department of Statistics, University of Wisconsin-Madison, WI

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Qiongshi Lu

1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI

2Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI

3Department of Statistics, University of Wisconsin-Madison, WI

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For correspondence: qlu@biostat.wisc.edu

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Posted November 07, 2022.

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Optimizing and benchmarking polygenic risk scores with GWAS summary statistics

Zijie Zhao, Tim Gruenloh, Yixuan Wu, Zhongxuan Sun, Jiacheng Miao, Yuchang Wu, Jie Song, Qiongshi Lu

bioRxiv 2022.10.26.513833; doi: https://doi.org/10.1101/2022.10.26.513833

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Optimizing and benchmarking polygenic risk scores with GWAS summary statistics

Zijie Zhao, Tim Gruenloh, Yixuan Wu, Zhongxuan Sun, Jiacheng Miao, Yuchang Wu, Jie Song, Qiongshi Lu

bioRxiv 2022.10.26.513833; doi: https://doi.org/10.1101/2022.10.26.513833

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