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用于检测人类复杂特征中存在的多效性的统计方法。

Statistical methods to detect pleiotropy in human complex traits.

机构信息

Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK.

Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK

出版信息

Open Biol. 2017 Nov;7(11). doi: 10.1098/rsob.170125.

DOI:10.1098/rsob.170125
PMID:29093210
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5717338/
Abstract

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.

摘要

近年来,多效性(一个遗传位点影响多个性状的现象)已成为人类遗传学中一个广泛研究的领域。随着全基因组关联研究汇总统计数据的日益普及,以及深度表型样本集的建立,现在可以系统地评估多个性状和疾病之间的遗传重叠。除了提高检测相关变异的能力外,多性状方法还可以通过突出相关的生物学途径,帮助我们了解不同疾病在病因上是如何相互关联的。目前有许多可用于进行此类分析的工具,每种工具都有其自身的优点和局限性。在这篇综述中,我们概述了一些目前可用于进行多性状分析的方法。首先,我们简要介绍多效性的概念,并概述人类遗传学中多效性研究的现状;其次,我们描述分析注意事项和分析方法;最后,我们讨论该领域的未来方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d1/5717338/a9645fdef1c3/rsob-7-170125-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d1/5717338/973dcd95e966/rsob-7-170125-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d1/5717338/a9645fdef1c3/rsob-7-170125-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d1/5717338/973dcd95e966/rsob-7-170125-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d1/5717338/a9645fdef1c3/rsob-7-170125-g2.jpg

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