Academic Journal

Demographic inference through approximate-Bayesian-computation skyline plots

التفاصيل البيبلوغرافية
العنوان: Demographic inference through approximate-Bayesian-computation skyline plots
المؤلفون: Miguel Navascués, Raphaël Leblois, Concetta Burgarella
المصدر: PeerJ, Vol 5, p e3530 (2017)
بيانات النشر: PeerJ Inc., 2017.
سنة النشر: 2017
المجموعة: LCC:Medicine
LCC:Biology (General)
مصطلحات موضوعية: Microsatellites, Population genetics, Population size change, Generalized stepwise mutation model, Approximate Bayesian computation, Medicine, Biology (General), QH301-705.5
الوصف: The skyline plot is a graphical representation of historical effective population sizes as a function of time. Past population sizes for these plots are estimated from genetic data, without a priori assumptions on the mathematical function defining the shape of the demographic trajectory. Because of this flexibility in shape, skyline plots can, in principle, provide realistic descriptions of the complex demographic scenarios that occur in natural populations. Currently, demographic estimates needed for skyline plots are estimated using coalescent samplers or a composite likelihood approach. Here, we provide a way to estimate historical effective population sizes using an Approximate Bayesian Computation (ABC) framework. We assess its performance using simulated and actual microsatellite datasets. Our method correctly retrieves the signal of contracting, constant and expanding populations, although the graphical shape of the plot is not always an accurate representation of the true demographic trajectory, particularly for recent changes in size and contracting populations. Because of the flexibility of ABC, similar approaches can be extended to other types of data, to multiple populations, or to other parameters that can change through time, such as the migration rate.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2167-8359
Relation: https://peerj.com/articles/3530.pdf; https://peerj.com/articles/3530/; https://doaj.org/toc/2167-8359
DOI: 10.7717/peerj.3530
URL الوصول: https://doaj.org/article/21b58f8fe9be451bb3449403365fd923
رقم الانضمام: edsdoj.21b58f8fe9be451bb3449403365fd923
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21678359
DOI:10.7717/peerj.3530