Demographic inference through approximate-Bayesian-computation skyline plots

13Citations
Citations of this article
90Readers
Mendeley users who have this article in their library.

Abstract

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.

References Powered by Scopus

Bayesian coalescent inference of past population dynamics from molecular sequences

2536Citations
N/AReaders
Get full text

Inference of human population history from individual whole-genome sequences

1690Citations
N/AReaders
Get full text

Detection of reduction in population size using data from microsatellite loci

1390Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation

39Citations
N/AReaders
Get full text

Multilevel rejection sampling for approximate Bayesian computation

22Citations
N/AReaders
Get full text

Sea ice reduction drives genetic differentiation among Barents Sea polar bears

14Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Navascués, M., Leblois, R., & Burgarella, C. (2017). Demographic inference through approximate-Bayesian-computation skyline plots. PeerJ, 2017(7). https://doi.org/10.7717/peerj.3530

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 42

59%

Researcher 20

28%

Professor / Associate Prof. 7

10%

Lecturer / Post doc 2

3%

Readers' Discipline

Tooltip

Agricultural and Biological Sciences 48

64%

Biochemistry, Genetics and Molecular Bi... 20

27%

Environmental Science 6

8%

Computer Science 1

1%

Save time finding and organizing research with Mendeley

Sign up for free