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Related Experiment Video

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

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Published on: February 3, 2023

fastsimcoal2: demographic inference under complex evolutionary scenarios.

Laurent Excoffier^1,2, Nina Marchi^1,2, David Alexander Marques^3,4,5

¹Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland.

Bioinformatics (Oxford, England)

|June 24, 2021

Summary

fastsimcoal2 enhances genetic simulations for complex population demography. It enables maximum-likelihood estimation of demographic parameters using site frequency spectra, improving population genetics research.

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Area of Science:

Population Genetics
Computational Biology
Evolutionary Biology

Background:

Coalescent-based genetic simulation is crucial for understanding population history.
Estimating demographic parameters from genetic data presents computational challenges, especially for complex scenarios.

Purpose of the Study:

To introduce fastsimcoal2, an advanced program for simulating genetic data and estimating demographic parameters.
To extend the capabilities of fastsimcoal for analyzing complex population structures and demographic histories.

Main Methods:

Utilizes a maximum-likelihood framework to estimate demographic parameters.
Employs a continuous-time coalescent-based simulation approach.
Leverages site frequency spectra for parameter estimation.

Main Results:

fastsimcoal2 enables estimation of demographic parameters under complex scenarios.
Improved efficiency for simulating sparsely structured populations and large chromosomes.
Enhanced features include multi-threading and handling of population inbreeding.

Conclusions:

fastsimcoal2 provides a powerful and flexible tool for population geneticists.
The software facilitates more accurate demographic inference from genetic data.
Its availability and comprehensive documentation support broad research applications.