Inference of multiple-wave admixtures by length distribution of ancestral tracks

doi:10.1038/s41437-017-0041-2

CSpace > 应用数学研究所

	Inference of multiple-wave admixtures by length distribution of ancestral tracks
	Ni, Xumin 1; Yuan, Kai 2,3; Yang, Xiong 2; Feng, Qidi 2,3; Guo, Wei 4; Ma, Zhiming1,4 ; Xu, Shuhua 2,3,5,6
	2018-07-01
发表期刊	HEREDITY
ISSN	0018-067X
卷号	121 期号:1 页码:52-63
摘要	The ancestral tracks in admixed genomes are valuable for population history inference. While a few methods have been developed to infer admixture history based on ancestral tracks, these methods suffer the same flaw: only population admixture history under some specific models can be inferred. In addition, the inference of history might be biased or even unreliable if the specific model deviates from the real situation. To address this problem, we firstly proposed a general discrete admixture model to describe the admixture history with multiple ancestral populations and multiple-wave admixtures. We next deduced the length distribution of ancestral tracks under the general discrete admixture model. We further developed a new method, MultiWaver, to explore multiple-wave admixture histories. Our method could automatically determine an optimal admixture model based on the length distribution of ancestral tracks, and estimate the corresponding parameters under this optimal model. Specifically, we used a likelihood ratio test (LRT) to determine the number of admixture waves, and implemented an expectation-maximization (EM) algorithm to estimate parameters. We used simulation studies to validate the reliability and effectiveness of our method. Finally, good performance was observed when our method was applied to real data sets of African Americans and Mexicans, and new insights were gained into the admixture history of Uyghurs and Hazaras.
DOI	10.1038/s41437-017-0041-2
语种	英语
资助项目	Strategic Priority Research Program[XDB13040100] ; Key Research Program of Frontier Sciences of the Chinese Academy of Sciences (CAS)[QYZDJ-SSW-SYS009] ; National Natural Science Foundation of China (NSFC)[91331204] ; National Natural Science Foundation of China (NSFC)[91731303] ; National Natural Science Foundation of China (NSFC)[31771388] ; National Natural Science Foundation of China (NSFC)[11426237] ; National Natural Science Foundation of China (NSFC)[31711530221] ; National Science Fund for Distinguished Young Scholars[31525014] ; Program of Shanghai Academic Research Leader[16XD1404700] ; 973 Project[2011CB808000] ; Fundamental Research Funds for the Central Universities[2017JBM071] ; Fundamental Research Funds for the Central Universities[2015IBM099] ; National Excellent Doctoral Dissertation Foundation of PR China[201213] ; National Center for Mathematics and Interdisciplinary Sciences of CAS ; Key Laboratory of Random Complex Structures and Data Science, CAS[2008DP173182] ; National Program for Top-Notch Young Innovative Talents of the "Wanren Jihua" Project
WOS研究方向	Environmental Sciences & Ecology ; Evolutionary Biology ; Genetics & Heredity
WOS类目	Ecology ; Evolutionary Biology ; Genetics & Heredity
WOS记录号	WOS:000434984600005
出版者	NATURE PUBLISHING GROUP
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/30515
专题	应用数学研究所
通讯作者	Ma, Zhiming; Xu, Shuhua
作者单位	1.Beijing Jiaotong Univ, Sch Sci, Dept Math, Beijing, Peoples R China 2.Chinese Acad Sci, Shanghai Inst Biol Sci, Key Lab Computat Biol,PICB, Max Planck Independent Res Grp Populat Genom,MPG, Shanghai, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing, Peoples R China 5.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China 6.Collaborat Innovat Ctr Genet & Dev, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Ni, Xumin,Yuan, Kai,Yang, Xiong,et al. Inference of multiple-wave admixtures by length distribution of ancestral tracks[J]. HEREDITY,2018,121(1):52-63.
APA	Ni, Xumin.,Yuan, Kai.,Yang, Xiong.,Feng, Qidi.,Guo, Wei.,...&Xu, Shuhua.(2018).Inference of multiple-wave admixtures by length distribution of ancestral tracks.HEREDITY,121(1),52-63.
MLA	Ni, Xumin,et al."Inference of multiple-wave admixtures by length distribution of ancestral tracks".HEREDITY 121.1(2018):52-63.