KMS Of Academy of mathematics and systems sciences, CAS
Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference | |
Ni, Xumin1; Yang, Xiong2; Guo, Wei3; Yuan, Kai2; Zhou, Ying2; Ma, Zhiming3![]() | |
2016-01-28 | |
Source Publication | SCIENTIFIC REPORTS
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ISSN | 2045-2322 |
Volume | 6Pages:12 |
Abstract | The length of ancestral tracks decays with the passing of generations which can be used to infer population admixture histories. Previous studies have shown the power in recovering the histories of admixed populations via the length distributions of ancestral tracks even under simple models. We believe that the deduction of length distributions under a general model will greatly elevate the power. Here we first deduced the length distributions under a general model and proposed general principles in parameter estimation and model selection with the deduced length distributions. Next, we focused on studying the length distributions and its applications under three typical special cases. Extensive simulations showed that the length distributions of ancestral tracks were well predicted by our theoretical framework. We further developed a new method, AdmixInfer, based on the length distributions and good performance was observed when it was applied to infer population histories under the three typical models. Notably, our method was insensitive to demographic history, sample size and threshold to discard short tracks. Finally, good performance was also observed when applied to some real datasets of African Americans, Mexicans and South Asian populations from the HapMap project and the Human Genome Diversity Project. |
DOI | 10.1038/srep20048 |
Language | 英语 |
Funding Project | Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB13040100] ; National Science Fund for Distinguished Young Scholars[31525014] ; National Natural Science Foundation of China (NSFC)[11426237] ; National Natural Science Foundation of China (NSFC)[91331204] ; National Natural Science Foundation of China (NSFC)[31171218] ; 973 Project[2011CB808000] ; Fundamental Research Funds for the Central Universities[2011JBZ019] ; Science and Technology Commission of Shanghai Municipality[14YF1406800] ; National Excellent Doctoral Dissertation Foundation of PR China[FANEDD 201312] ; 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 Research Area | Science & Technology - Other Topics |
WOS Subject | Multidisciplinary Sciences |
WOS ID | WOS:000368786700001 |
Publisher | NATURE PUBLISHING GROUP |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/21838 |
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, Key Lab Computat Biol, Max Planck Independent Res Grp Populat Genom, Shanghai Inst Biol Sci,CAS MPG Partner Inst Compu, Shanghai 200031, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing 100190, Peoples R China 4.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 200031, Peoples R China 5.Collaborat Innovat Ctr Genet & Dev, Shanghai 200438, Peoples R China |
Recommended Citation GB/T 7714 | Ni, Xumin,Yang, Xiong,Guo, Wei,et al. Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference[J]. SCIENTIFIC REPORTS,2016,6:12. |
APA | Ni, Xumin.,Yang, Xiong.,Guo, Wei.,Yuan, Kai.,Zhou, Ying.,...&Xu, Shuhua.(2016).Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference.SCIENTIFIC REPORTS,6,12. |
MLA | Ni, Xumin,et al."Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference".SCIENTIFIC REPORTS 6(2016):12. |
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