畜牧兽医学报 ›› 2016, Vol. 47 ›› Issue (2): 213-217.doi: 10.11843/j.issn.0366-6964.2016.02.001

• 综述 • 上一篇    下一篇

全基因组关联分析方法的研究进展

郝兴杰,胡林,张淑君*   

  1. (华中农业大学动物科学技术学院/动物医学院 动物遗传育种与繁殖教育部重点实验室,武汉 430070)
  • 收稿日期:2015-06-01 出版日期:2016-02-23 发布日期:2016-02-23
  • 通讯作者: 张淑君,教授,E-mail:sjxiaozhang@mail.hzau.edu.cn
  • 作者简介:郝兴杰(1990-),男,湖北南漳人,博士,主要从事动物遗传疾病的研究,E-mail:xingjiehao@webmail.hzau.edu.cn
  • 基金资助:

    促进与美大地区科研合作与高层次人才培养项目(52902-0650104);欧盟FPT构架项目玛丽居里夫人人才基金(Marie Curie Action,P11FR-GA-2012-912205)

Progresses in Research of Genome-wide Association Study Methods

HAO Xing-jie,HU Lin,ZHANG Shu-jun*   

  1. (Key Laboratory of Animal Breeding and Reproduction of Ministry of Education,College of Animal Science and Technology/College of Veterinary Medicine,Huazhong Agricultural University,Wuhan 430070,China)
  • Received:2015-06-01 Online:2016-02-23 Published:2016-02-23

摘要:

全基因组关联分析目前已经成为研究复杂性状和疾病遗传变异的有效方法,但是由于群体结构的存在,导致分析结果出现虚假关联。经过数十年的发展,各种新方法不断出现和完善,用于减少群体结构对分析的影响。本综述将对在全基因组关联分析中能够处理群体结构的方法进行介绍,以期为进一步选择GWAS方法准确揭示各种性状的遗传背景提供参考。

Abstract:

The genome-wide association study (GWAS) has become an effective approach to identify genetic variants associated with complex traits and diseases.However,population structure can result in spurious association.In the past few decades,new approaches were developed and improved to minimize the influence of population structure.In this review,we summarize some new approaches to treat population structure for selecting the best method for any GWAS to reveal the genetic backgroud of some traits.

中图分类号: