title: SLiM 2: Flexible, Interactive Forward Genetic Simulations.
abstract: 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.
authors.affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY bhaller@benhaller.com messer@cornell.edu.
authors.forename: Benjamin C
authors.initials: BC
authors.lastname: Haller
authors.affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY bhaller@benhaller.com messer@cornell.edu.
authors.forename: Philipp W
authors.initials: PW
authors.lastname: Messer
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D003198:Computer Simulation; D005828:Genetics, Population / Q000379:methods*; D023281:Genomics; D056186:Metagenomics / Q000379:methods*; D008957:Models, Genetic; D012984:Software
keywords: ecological modeling; evolutionary modeling; forward genetic simulation; population genomics; software