Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes

Information of genetic architectures of complex traits can be leveraged for predicting phenotypes. Here, the authors develop CTPR (Cross-Trait Penalized Regression), a method for multi-trait polygenic risk prediction using individual-level genotypes and/or summary statistics from large cohorts.

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Autores principales:	Wonil Chung, Jun Chen, Constance Turman, Sara Lindstrom, Zhaozhong Zhu, Po-Ru Loh, Peter Kraft, Liming Liang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/bff51525773547649c9ec281d7ff076f
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spelling	oai:doaj.org-article:bff51525773547649c9ec281d7ff076f2021-12-02T14:38:42ZEfficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes10.1038/s41467-019-08535-02041-1723https://doaj.org/article/bff51525773547649c9ec281d7ff076f2019-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-08535-0https://doaj.org/toc/2041-1723Information of genetic architectures of complex traits can be leveraged for predicting phenotypes. Here, the authors develop CTPR (Cross-Trait Penalized Regression), a method for multi-trait polygenic risk prediction using individual-level genotypes and/or summary statistics from large cohorts.Wonil ChungJun ChenConstance TurmanSara LindstromZhaozhong ZhuPo-Ru LohPeter KraftLiming LiangNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-11 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Wonil Chung Jun Chen Constance Turman Sara Lindstrom Zhaozhong Zhu Po-Ru Loh Peter Kraft Liming Liang Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
description	Information of genetic architectures of complex traits can be leveraged for predicting phenotypes. Here, the authors develop CTPR (Cross-Trait Penalized Regression), a method for multi-trait polygenic risk prediction using individual-level genotypes and/or summary statistics from large cohorts.
format	article
author	Wonil Chung Jun Chen Constance Turman Sara Lindstrom Zhaozhong Zhu Po-Ru Loh Peter Kraft Liming Liang
author_facet	Wonil Chung Jun Chen Constance Turman Sara Lindstrom Zhaozhong Zhu Po-Ru Loh Peter Kraft Liming Liang
author_sort	Wonil Chung
title	Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
title_short	Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
title_full	Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
title_fullStr	Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
title_full_unstemmed	Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
title_sort	efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/bff51525773547649c9ec281d7ff076f
work_keys_str_mv	AT wonilchung efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT junchen efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT constanceturman efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT saralindstrom efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT zhaozhongzhu efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT poruloh efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT peterkraft efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes AT limingliang efficientcrosstraitpenalizedregressionincreasespredictionaccuracyinlargecohortsusingsecondaryphenotypes
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Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes

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