A general and efficient representation of ancestral recombination graphs

Author:

Wong Yan1ORCID,Ignatieva Anastasia23ORCID,Koskela Jere45ORCID,Gorjanc Gregor6ORCID,Wohns Anthony W78ORCID,Kelleher Jerome1ORCID

Affiliation:

1. Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford , Oxford OX3 7LF , UK

2. School of Mathematics and Statistics, University of Glasgow , Glasgow G12 8TA , UK

3. Department of Statistics, University of Oxford , Oxford OX1 3LB , UK

4. School of Mathematics, Statistics and Physics, Newcastle University , Newcastle NE1 7RU , UK

5. Department of Statistics, University of Warwick , Coventry CV4 7AL , UK

6. The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh , Edinburgh EH25 9RG , UK

7. Broad Institute of MIT and Harvard , Cambridge, MA 02142 , USA

8. Department of Genetics, Stanford University School of Medicine , Stanford, CA 94305-5101 , USA

Abstract

Abstract As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. However, this approach is out of step with some modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalizes these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

Funder

BBSRC

Robertson Foundation

NIH

EPSRC

Publisher

Oxford University Press (OUP)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3