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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Royal Society
2017
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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. |
format | Online Article Text |
id | pubmed-5717338 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT hackingersophie statisticalmethodstodetectpleiotropyinhumancomplextraits AT zegginieleftheria statisticalmethodstodetectpleiotropyinhumancomplextraits |