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SMARTPOP: Inferring the impact of social dynamics on genetic diversity through high speed simulations

Cox, Murray P.; Guillot, Elsa G.; Guillot, Elsa; Cox, Murray P


Murray P. Cox

Elsa G. Guillot

Elsa Guillot

Murray P Cox


Background: Social behavior has long been known to influence patterns of genetic diversity, but the effect of social processes on population genetics remains poorly quantified - partly due to limited community-level genetic sampling (which is increasingly being remedied), and partly to a lack of fast simulation software to jointly model genetic evolution and complex social behavior, such as marriage rules.Results: To fill this gap, we have developed SMARTPOP - a fast, forward-in-time genetic simulator - to facilitate large-scale statistical inference on interactions between social factors, such as mating systems, and population genetic diversity. By simultaneously modeling genetic inheritance and dynamic social processes at the level of the individual, SMARTPOP can simulate a wide range of genetic systems (autosomal, X-linked, Y chromosomal and mitochondrial DNA) under a range of mating systems and demographic models. Specifically designed to enable resource-intensive statistical inference tasks, such as Approximate Bayesian Computation, SMARTPOP has been coded in C++ and is heavily optimized for speed and reduced memory usage.Conclusion: SMARTPOP rapidly simulates population genetic data under a wide range of demographic scenarios and social behaviors, thus allowing quantitative analyses to address complex socio-ecological questions. © 2014 Guillot and Cox; licensee BioMed Central Ltd.


Cox, M. P., Guillot, E. G., Guillot, E., & Cox, M. P. (2014). SMARTPOP: Inferring the impact of social dynamics on genetic diversity through high speed simulations. BMC Bioinformatics, 15(1), 175.

Journal Article Type Article
Acceptance Date Jun 3, 2014
Publication Date Jun 9, 2014
Journal BMC Bioinformatics
Electronic ISSN 1471-2105
Publisher BMC
Peer Reviewed Peer Reviewed
Volume 15
Issue 1
Pages 175
Keywords population genetics, mating systems, forward-in-time simulation
Public URL
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