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
Sujets:	Science Q
Accès en ligne:	https://doaj.org/article/f563b6a1c3d34087b48dd7004f4f0993
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Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics

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