Multi-resolution localization of causal variants across the genome

GWAS analysis currently relies mostly on linear mixed models, which do not account for linkage disequilibrium (LD) between tested variants. Here, Sesia et al. propose KnockoffZoom, a non-parametric statistical method for the simultaneous discovery and fine-mapping of causal variants, assuming only t...

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Autores principales:	Matteo Sesia, Eugene Katsevich, Stephen Bates, Emmanuel Candès, Chiara Sabatti
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/5a6f10c7c51540a6bf620c7a5cb1956c
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id	oai:doaj.org-article:5a6f10c7c51540a6bf620c7a5cb1956c
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spelling	oai:doaj.org-article:5a6f10c7c51540a6bf620c7a5cb1956c2021-12-02T16:50:00ZMulti-resolution localization of causal variants across the genome10.1038/s41467-020-14791-22041-1723https://doaj.org/article/5a6f10c7c51540a6bf620c7a5cb1956c2020-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-14791-2https://doaj.org/toc/2041-1723GWAS analysis currently relies mostly on linear mixed models, which do not account for linkage disequilibrium (LD) between tested variants. Here, Sesia et al. propose KnockoffZoom, a non-parametric statistical method for the simultaneous discovery and fine-mapping of causal variants, assuming only that LD is described by hidden Markov models (HMMs).Matteo SesiaEugene KatsevichStephen BatesEmmanuel CandèsChiara SabattiNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Matteo Sesia Eugene Katsevich Stephen Bates Emmanuel Candès Chiara Sabatti Multi-resolution localization of causal variants across the genome
description	GWAS analysis currently relies mostly on linear mixed models, which do not account for linkage disequilibrium (LD) between tested variants. Here, Sesia et al. propose KnockoffZoom, a non-parametric statistical method for the simultaneous discovery and fine-mapping of causal variants, assuming only that LD is described by hidden Markov models (HMMs).
format	article
author	Matteo Sesia Eugene Katsevich Stephen Bates Emmanuel Candès Chiara Sabatti
author_facet	Matteo Sesia Eugene Katsevich Stephen Bates Emmanuel Candès Chiara Sabatti
author_sort	Matteo Sesia
title	Multi-resolution localization of causal variants across the genome
title_short	Multi-resolution localization of causal variants across the genome
title_full	Multi-resolution localization of causal variants across the genome
title_fullStr	Multi-resolution localization of causal variants across the genome
title_full_unstemmed	Multi-resolution localization of causal variants across the genome
title_sort	multi-resolution localization of causal variants across the genome
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/5a6f10c7c51540a6bf620c7a5cb1956c
work_keys_str_mv	AT matteosesia multiresolutionlocalizationofcausalvariantsacrossthegenome AT eugenekatsevich multiresolutionlocalizationofcausalvariantsacrossthegenome AT stephenbates multiresolutionlocalizationofcausalvariantsacrossthegenome AT emmanuelcandes multiresolutionlocalizationofcausalvariantsacrossthegenome AT chiarasabatti multiresolutionlocalizationofcausalvariantsacrossthegenome
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Multi-resolution localization of causal variants across the genome

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