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A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration
Ni, Xumin1; Guo, Wei2; Yuan, Kai3; Yang, Xiong3; Ma, Zhiming2; Xu, Shuhua3,4,5; Zhang, Shihua2
2016-03-01
发表期刊IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
ISSN1545-5963
卷号13期号:2页码:281-290
摘要The inference of demographic history of populations is an important undertaking in population genetics. A few recent studies have developed identity-by-descent (IBD) based methods to reveal the signature of the relatively recent historical events. Notably, Pe'er and his colleagues have introduced a novel method (named PIBD here) by employing IBD sharing to infer effective population size and migration rate. However, under island model, PIBD neglects the coalescent information before the time to the most recent common ancestor (tMRCA) which leads to apparent deviations in certain situations. In this paper, we propose a new method, MIBD, by adopting a Markov process to describe the island model and develop a new formula for estimating IBD sharing. The new formula considers the coalescent information before tMRCA and the joint effect of the coalescent and migration events. We apply both MIBD and PIBD to the genome-wide data of two human populations (Palestinian and Bedouin) obtained from the HGDP-CEPH database, and demonstrate that MIBD is competitive to PIBD. Our simulation analyses also show that the results of MIBD are more accurate than those of PIBD especially in the case of small effective population size.
关键词Population genetics identity by descent probabilistic method Markov process
DOI10.1109/TCBB.2015.2480074
语种英语
资助项目National Natural Science Foundation of China (NSFC)[11426237] ; National Natural Science Foundation of China (NSFC)[91331204] ; National Natural Science Foundation of China (NSFC)[31171218] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB13040100] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB13040600] ; 973 Project[2011CB808000] ; Fundamental Research Funds for the Central Universities[2011JBZ019] ; National Excellent Doctoral Dissertation Foundation of PR China (FANEDD)[201312] ; Key Laboratory of Random Complex Structures and Data Science, CAS[2008DP173182] ; National Program for Top-notch Young Innovative Talents of The "Wanren Jihua" Project ; Outstanding Young Scientist Program of CAS, National Center for Mathematics and Interdisciplinary Sciences of CAS
WOS研究方向Biochemistry & Molecular Biology ; Computer Science ; Mathematics
WOS类目Biochemical Research Methods ; Computer Science, Interdisciplinary Applications ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS记录号WOS:000374305300009
出版者IEEE COMPUTER SOC
引用统计
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/22526
专题应用数学研究所
通讯作者Ni, Xumin; Guo, Wei; Yuan, Kai; Yang, Xiong; Ma, Zhiming; Xu, Shuhua; Zhang, Shihua
作者单位1.Beijing Jiaotong Univ, Dept Math, Sch Sci, Beijing 100044, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Shanghai Inst Biol Sci, Max Planck Independent Res Grp Populat Genom, CAS MPG Partner Inst Computat Biol, Shanghai 200031, Peoples R China
4.ShanghaiTec Univ, Sch Life Sci & Technol, Shanghai 200031, Peoples R China
5.Collaborat Innovat Ctr Genet & Dev, Shanghai 200438, Peoples R China
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Ni, Xumin,Guo, Wei,Yuan, Kai,et al. A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration[J]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,2016,13(2):281-290.
APA Ni, Xumin.,Guo, Wei.,Yuan, Kai.,Yang, Xiong.,Ma, Zhiming.,...&Zhang, Shihua.(2016).A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration.IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,13(2),281-290.
MLA Ni, Xumin,et al."A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration".IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 13.2(2016):281-290.
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