Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives

Genetic data from large cohorts of unrelated individuals can be used to create polygenic risk scores, which could be used to predict individual risk of developing a specific disease. Here the authors show that smaller cohorts of related individuals can provide similarly powerful predictive ability.

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Autores principales:	Buu Truong, Xuan Zhou, Jisu Shin, Jiuyong Li, Julius H. J. van der Werf, Thuc D. Le, S. Hong Lee
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/08755dc1466a43b28f5affeeb522ac79
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spelling	oai:doaj.org-article:08755dc1466a43b28f5affeeb522ac792021-12-02T16:04:17ZEfficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives10.1038/s41467-020-16829-x2041-1723https://doaj.org/article/08755dc1466a43b28f5affeeb522ac792020-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-16829-xhttps://doaj.org/toc/2041-1723Genetic data from large cohorts of unrelated individuals can be used to create polygenic risk scores, which could be used to predict individual risk of developing a specific disease. Here the authors show that smaller cohorts of related individuals can provide similarly powerful predictive ability.Buu TruongXuan ZhouJisu ShinJiuyong LiJulius H. J. van der WerfThuc D. LeS. Hong LeeNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Buu Truong Xuan Zhou Jisu Shin Jiuyong Li Julius H. J. van der Werf Thuc D. Le S. Hong Lee Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
description	Genetic data from large cohorts of unrelated individuals can be used to create polygenic risk scores, which could be used to predict individual risk of developing a specific disease. Here the authors show that smaller cohorts of related individuals can provide similarly powerful predictive ability.
format	article
author	Buu Truong Xuan Zhou Jisu Shin Jiuyong Li Julius H. J. van der Werf Thuc D. Le S. Hong Lee
author_facet	Buu Truong Xuan Zhou Jisu Shin Jiuyong Li Julius H. J. van der Werf Thuc D. Le S. Hong Lee
author_sort	Buu Truong
title	Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
title_short	Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
title_full	Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
title_fullStr	Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
title_full_unstemmed	Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
title_sort	efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/08755dc1466a43b28f5affeeb522ac79
work_keys_str_mv	AT buutruong efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives AT xuanzhou efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives AT jisushin efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives AT jiuyongli efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives AT juliushjvanderwerf efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives AT thucdle efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives AT shonglee efficientpolygenicriskscoresforbiobankscaledatabyexploitingphenotypesfrominferredrelatives
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Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives

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