Inference of multiple-wave admixtures by length distribution of ancestral tracks
文献类型：期刊论文
| 作者 | Ni, Xumin1; Yuan, Kai2,3; Yang, Xiong2; Feng, Qidi2,3; Guo, Wei4; Ma, Zhiming1,4 ; Xu, Shuhua2,3,5,6
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| 刊名 | HEREDITY
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| 出版日期 | 2018-07-01 |
| 卷号 | 121期号:1页码:52-63 |
| ISSN号 | 0018-067X |
| DOI | 10.1038/s41437-017-0041-2 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| 出版者 | NATURE PUBLISHING GROUP |
| WOS记录号 | WOS:000434984600005 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/30514]  |
| 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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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