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Mol Biol Evol. 2017 Jan;34(1):230-240. doi: 10.1093/molbev/msw211. Epub 2016 Oct 3.

SLiM 2: Flexible, Interactive Forward Genetic Simulations.

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Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY


Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages.


ecological modeling; evolutionary modeling; forward genetic simulation; population genomics; software

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