KMS Of Academy of mathematics and systems sciences, CAS
| MultiWaver 2.0: modeling discrete and continuous gene flow to reconstruct complex population admixtures | |
Ni, Xumin1; Yuan, Kai2,3; Liu, Chang2,3; Feng, Qidi2,3; Tian, Lei2,3; Ma, Zhiming1,3,4 ; Xu, Shuhua2,3,5,6,7
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| 2019 | |
| Source Publication | EUROPEAN JOURNAL OF HUMAN GENETICS
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| ISSN | 1018-4813 |
| Volume | 27Issue:1Pages:133-139 |
| Abstract | Our goal in developing the MultiWaver software series was to be able to infer population admixture history under various complex scenarios. The earlier version of MultiWaver considered only discrete admixture models. Here, we report a newly developed version, MultiWaver 2.0, that implements a more flexible framework and is capable of inferring multiple-wave admixture histories under both discrete and continuous admixture models. MultiWaver 2.0 can automatically select an optimal admixture model based on the length distribution of ancestral tracks of chromosomes, and the program can estimate the corresponding parameters under the selected model. Specifically, for discrete admixture models, we used a likelihood ratio test (LRT) to determine the optimal discrete model and an expectation-maximization algorithm to estimate the parameters. In addition, according to the principles of the Bayesian Information Criterion (BIC), we compared the optimal discrete model with several continuous admixture models. In MultiWaver 2.0, we also applied a bootstrapping technique to provide levels of support for the chosen model and the confidence interval (CI) of the estimations of admixture time. Simulation studies validated the reliability and effectiveness of our method. Finally, the program performed well when applied to real datasets of typical admixed populations, such as African Americans, Uyghurs, and Hazaras. |
| DOI | 10.1038/s41431-018-0259-3 |
| Language | 英语 |
| Funding Project | Strategic Priority Research Program[XDB13040100] ; Key Research Program of Frontier Sciences of the Chinese Academy of Sciences (CAS)[QYZDJ-SSW-SYS009] ; Fundamental Research Funds for the Central Universities[2017JBM071] ; Fundamental Research Funds for the Central Universities[2017YJS197] ; 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] ; National Key Research and Development Program[2016YFC0906403] ; Shanghai Municipal Science and Technology Major Project[2017SHZDZX01] ; China Postdoctoral Science Foundation[2017M620595] ; National Center for Mathematics and Interdisciplinary Sciences of CAS ; National Program for Top-Notch Young Innovative Talents of the "Wanren Jihua" Project |
| WOS Research Area | Biochemistry & Molecular Biology ; Genetics & Heredity |
| WOS Subject | Biochemistry & Molecular Biology ; Genetics & Heredity |
| WOS ID | WOS:000454111500016 |
| Publisher | NATURE PUBLISHING GROUP |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/31894 |
| Collection | 应用数学研究所 |
| Corresponding Author | Ma, Zhiming; Xu, Shuhua |
| Affiliation | 1.Beijing Jiaotong Univ, Sch Sci, Dept Math, Beijing 100044, Peoples R China 2.Chinese Acad Sci, MPG Partner Inst Computat Biol PICB, Shanghai Inst Nutr & Hlth,Shanghai Inst Biol Sci, Key Lab Computat Biol,Max Planck Independent Res, Shanghai 200031, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 5.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China 6.Chinese Acad Sci, Ctr Excellence Anim Evolut & Genet, Kunming 650223, Yunnan, Peoples R China 7.Collaborat Innovat Ctr Genet & Dev, Shanghai 200438, Peoples R China |
| Recommended Citation GB/T 7714 | Ni, Xumin,Yuan, Kai,Liu, Chang,et al. MultiWaver 2.0: modeling discrete and continuous gene flow to reconstruct complex population admixtures[J]. EUROPEAN JOURNAL OF HUMAN GENETICS,2019,27(1):133-139. |
| APA | Ni, Xumin.,Yuan, Kai.,Liu, Chang.,Feng, Qidi.,Tian, Lei.,...&Xu, Shuhua.(2019).MultiWaver 2.0: modeling discrete and continuous gene flow to reconstruct complex population admixtures.EUROPEAN JOURNAL OF HUMAN GENETICS,27(1),133-139. |
| MLA | Ni, Xumin,et al."MultiWaver 2.0: modeling discrete and continuous gene flow to reconstruct complex population admixtures".EUROPEAN JOURNAL OF HUMAN GENETICS 27.1(2019):133-139. |
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