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Statistical methods to detect pleiotropy in human complex traits

In recent years pleiotropy, the phenomenon of one genetic locus influencing several traits, has become a widely researched field in human genetics. With the increasing availability of genome-wide association study summary statistics, as well as the establishment of deeply phenotyped sample collectio...

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Detalles Bibliográficos
Autores principales: Hackinger, Sophie, Zeggini, Eleftheria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5717338/
https://www.ncbi.nlm.nih.gov/pubmed/29093210
http://dx.doi.org/10.1098/rsob.170125
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author Hackinger, Sophie
Zeggini, Eleftheria
author_facet Hackinger, Sophie
Zeggini, Eleftheria
author_sort Hackinger, Sophie
collection PubMed
description In recent years pleiotropy, the phenomenon of one genetic locus influencing several traits, has become a widely researched field in human genetics. With the increasing availability of genome-wide association study summary statistics, as well as the establishment of deeply phenotyped sample collections, it is now possible to systematically assess the genetic overlap between multiple traits and diseases. In addition to increasing power to detect associated variants, multi-trait methods can also aid our understanding of how different disorders are aetiologically linked by highlighting relevant biological pathways. A plethora of available tools to perform such analyses exists, each with their own advantages and limitations. In this review, we outline some of the currently available methods to conduct multi-trait analyses. First, we briefly introduce the concept of pleiotropy and outline the current landscape of pleiotropy research in human genetics; second, we describe analytical considerations and analysis methods; finally, we discuss future directions for the field.
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spelling pubmed-57173382017-12-14 Statistical methods to detect pleiotropy in human complex traits Hackinger, Sophie Zeggini, Eleftheria Open Biol Review In recent years pleiotropy, the phenomenon of one genetic locus influencing several traits, has become a widely researched field in human genetics. With the increasing availability of genome-wide association study summary statistics, as well as the establishment of deeply phenotyped sample collections, it is now possible to systematically assess the genetic overlap between multiple traits and diseases. In addition to increasing power to detect associated variants, multi-trait methods can also aid our understanding of how different disorders are aetiologically linked by highlighting relevant biological pathways. A plethora of available tools to perform such analyses exists, each with their own advantages and limitations. In this review, we outline some of the currently available methods to conduct multi-trait analyses. First, we briefly introduce the concept of pleiotropy and outline the current landscape of pleiotropy research in human genetics; second, we describe analytical considerations and analysis methods; finally, we discuss future directions for the field. The Royal Society 2017-11-01 /pmc/articles/PMC5717338/ /pubmed/29093210 http://dx.doi.org/10.1098/rsob.170125 Text en © 2017 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Review
Hackinger, Sophie
Zeggini, Eleftheria
Statistical methods to detect pleiotropy in human complex traits
title Statistical methods to detect pleiotropy in human complex traits
title_full Statistical methods to detect pleiotropy in human complex traits
title_fullStr Statistical methods to detect pleiotropy in human complex traits
title_full_unstemmed Statistical methods to detect pleiotropy in human complex traits
title_short Statistical methods to detect pleiotropy in human complex traits
title_sort statistical methods to detect pleiotropy in human complex traits
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5717338/
https://www.ncbi.nlm.nih.gov/pubmed/29093210
http://dx.doi.org/10.1098/rsob.170125
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