Yang, Xiong and Yuan, Kai and Ni, Xumin and Zhou, Ying and Guo, Wei and Xu, Shuhua (2020) AdmixSim: A Forward-Time Simulator for Various Complex Scenarios of Population Admixture. Frontiers in Genetics, 11. ISSN 1664-8021
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Abstract
Background: Population admixture is a common phenomenon in humans, animals, and plants, and it plays a very important role in shaping individual genetic architecture and population genetic diversity. Inference of population admixture, however, is very challenging and typically relies on in silico simulation. We are aware of the lack of a computerized tool for such a purpose. A simulator capable of generating data under various complex admixture scenarios would facilitate the study of recombination, linkage disequilibrium, ancestry tracing, and admixture dynamics in admixed populations. We described such a simulator here.
Results: We developed a forward-time simulator (AdmixSim) under the standard Wright Fisher model. It can simulate the following admixed populations: (1) multiple ancestral populations; (2) multiple waves of admixture events; (3) fluctuating population size; and (4) admixtures of fluctuating proportions. Analysis of the simulated data by AdmixSim showed that our simulator can quickly and accurately generate data resembling real-world values. We included in AdmixSim all possible parameters that would allow users to modify and simulate any kind of admixture scenario easily, so it is very flexible. AdmixSim records recombination break points and traces of each chromosomal segment from different ancestral populations, with which users can easily perform further analysis and comparative studies with empirical data.
Conclusions: AdmixSim facilitates the study of population admixture by providing a simulation framework with the flexible implementation of various admixture models and parameters.
Item Type: | Article |
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Subjects: | South Archive > Medical Science |
Depositing User: | Unnamed user with email support@southarchive.com |
Date Deposited: | 28 Jan 2023 09:19 |
Last Modified: | 29 Jul 2024 09:48 |
URI: | http://ebooks.eprintrepositoryarticle.com/id/eprint/114 |