遗传 ›› 2016, Vol. 38 ›› Issue (8): 707-717.doi: 10.16288/j.yczz.16-100

• 综述 • 上一篇    下一篇

群体遗传学模拟软件应用现状

高峰1, 2, 李海鹏1   

  1. 1. 中国科学院计算生物学重点实验室,中国科学院-德国马普学会计算生物学伙伴研究所,上海 200031;
    2. 中国科学院大学,北京100049
  • 收稿日期:2016-03-22 修回日期:2016-04-25 出版日期:2016-08-20 发布日期:2016-07-23
  • 通讯作者: 李海鹏,博士,研究员,研究方向:理论群体遗传学。E-mail: lihaipeng@picb.ac.cn E-mail:gaofeng@picb.ac.cn
  • 作者简介:高峰,博士,专业方向:生物信息学。E-mail: gaofeng@picb.ac.cn
  • 基金资助:
    中国科学院先导B项目(编号:XDB13040800)和国家自然科学基金项目(编号:91531306)资助

Application of computer simulators in population genetics

Feng Gao1, 2, Haipeng Li1   

  1. 1. CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai 200031, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2016-03-22 Revised:2016-04-25 Online:2016-08-20 Published:2016-07-23
  • Supported by:
    Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (No; XDB13040800) and the National Natural Science Foundation of China (No; 91531306)

摘要: 随着下一代测序技术的不断进步与测序价格的不断下降,越来越多物种的全基因组信息被公开。作为研究群体遗传变异模式工具之一的模拟软件必然将发挥越来越重要的作用。依据时间推演方向的不同,模拟软件可以分为依时间向前和向后推演,二者各有所长,功能上互相补充,分别适合于不同的模拟需求。这些软件在研究进化动力的影响、估计进化动力参数与验证不同进化假设以及新方法有效性等方面起着重要作用。本文简要介绍了群体遗传学相关理论知识,详细比较了近10年来发表的32款模拟软件,并对模拟软件的未来发展方向给出了建议。

关键词: 群体遗传学, 计算机模拟, 依时间向前, 依时间向后

Abstract: The genomes of more and more organisms have been sequenced due to the advances in next-generation sequencing technologies. As a powerful tool, computer simulators play a critical role in studying the genome-wide DNA polymorphism pattern. Simulations can be performed both forwards-in-time and backwards-in-time, which complement each other and are suitable for meeting different needs, such as studying the effect of evolutionary dynamics, the estimation of parameters, and the validation of evolutionary hypotheses as well as new methods. In this review, we briefly introduced population genetics related theoretical framework and provided a detailed comparison of 32 simulators published over the last ten years. The future development of new simulators was also discussed.

Key words: population genetics, computer simulation, forwards-in-time, backwards-in-time