Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction

The application of polygenic risk scores to individual-level disease susceptibility is challenging, as risk is evaluated at a group-level. Here, the authors describe a machine learning method, Mondrian Cross-Conformal Prediction, that reports disease status conditional probability value at the indiv...

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Autores principales: Jiangming Sun, Yunpeng Wang, Lasse Folkersen, Yan Borné, Inge Amlien, Alfonso Buil, Marju Orho-Melander, Anders D. Børglum, David M. Hougaard, Regeneron Genetics Center, Olle Melander, Gunnar Engström, Thomas Werge, Kasper Lage
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Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/1f27829d10184dee8d91f723afe0978e
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spelling oai:doaj.org-article:1f27829d10184dee8d91f723afe0978e2021-12-02T17:19:40ZTranslating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction10.1038/s41467-021-25014-72041-1723https://doaj.org/article/1f27829d10184dee8d91f723afe0978e2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-25014-7https://doaj.org/toc/2041-1723The application of polygenic risk scores to individual-level disease susceptibility is challenging, as risk is evaluated at a group-level. Here, the authors describe a machine learning method, Mondrian Cross-Conformal Prediction, that reports disease status conditional probability value at the individual level.Jiangming SunYunpeng WangLasse FolkersenYan BornéInge AmlienAlfonso BuilMarju Orho-MelanderAnders D. BørglumDavid M. HougaardRegeneron Genetics CenterOlle MelanderGunnar EngströmThomas WergeKasper LageNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Jiangming Sun
Yunpeng Wang
Lasse Folkersen
Yan Borné
Inge Amlien
Alfonso Buil
Marju Orho-Melander
Anders D. Børglum
David M. Hougaard
Regeneron Genetics Center
Olle Melander
Gunnar Engström
Thomas Werge
Kasper Lage
Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
description The application of polygenic risk scores to individual-level disease susceptibility is challenging, as risk is evaluated at a group-level. Here, the authors describe a machine learning method, Mondrian Cross-Conformal Prediction, that reports disease status conditional probability value at the individual level.
format article
author Jiangming Sun
Yunpeng Wang
Lasse Folkersen
Yan Borné
Inge Amlien
Alfonso Buil
Marju Orho-Melander
Anders D. Børglum
David M. Hougaard
Regeneron Genetics Center
Olle Melander
Gunnar Engström
Thomas Werge
Kasper Lage
author_facet Jiangming Sun
Yunpeng Wang
Lasse Folkersen
Yan Borné
Inge Amlien
Alfonso Buil
Marju Orho-Melander
Anders D. Børglum
David M. Hougaard
Regeneron Genetics Center
Olle Melander
Gunnar Engström
Thomas Werge
Kasper Lage
author_sort Jiangming Sun
title Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
title_short Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
title_full Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
title_fullStr Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
title_full_unstemmed Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
title_sort translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/1f27829d10184dee8d91f723afe0978e
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