Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics

Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics

Thus far, pleiotropy analysis using individual-level Electronic Health Records data has been limited to data from one site. Here, the authors introduce Sum-Share, a method designed to efficiently and losslessly integrate EHR and genetic data from multiple sites to perform pleiotropy analysis.

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Détails bibliographiques
Auteurs principaux: Ruowang Li, Rui Duan, Xinyuan Zhang, Thomas Lumley, Sarah Pendergrass, Christopher Bauer, Hakon Hakonarson, David S. Carrell, Jordan W. Smoller, Wei-Qi Wei, Robert Carroll, Digna R. Velez Edwards, Georgia Wiesner, Patrick Sleiman, Josh C. Denny, Jonathan D. Mosley, Marylyn D. Ritchie, Yong Chen, Jason H. Moore
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Science
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Accès en ligne:https://doaj.org/article/f563b6a1c3d34087b48dd7004f4f0993
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Internet

https://doaj.org/article/f563b6a1c3d34087b48dd7004f4f0993

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