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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Detalles Bibliográficos
Autores principales:	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
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/f563b6a1c3d34087b48dd7004f4f0993
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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spelling	oai:doaj.org-article:f563b6a1c3d34087b48dd7004f4f09932021-12-02T11:45:56ZLossless integration of multiple electronic health records for identifying pleiotropy using summary statistics10.1038/s41467-020-20211-22041-1723https://doaj.org/article/f563b6a1c3d34087b48dd7004f4f09932021-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-20211-2https://doaj.org/toc/2041-1723Thus 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.Ruowang LiRui DuanXinyuan ZhangThomas LumleySarah PendergrassChristopher BauerHakon HakonarsonDavid S. CarrellJordan W. SmollerWei-Qi WeiRobert CarrollDigna R. Velez EdwardsGeorgia WiesnerPatrick SleimanJosh C. DennyJonathan D. MosleyMarylyn D. RitchieYong ChenJason H. MooreNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q 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 Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
description	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.
format	article
author	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
author_facet	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
author_sort	Ruowang Li
title	Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
title_short	Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
title_full	Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
title_fullStr	Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
title_full_unstemmed	Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
title_sort	lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics
publisher	Nature Portfolio
publishDate	2021
url	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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