TY - JOUR TI - A community-maintained standard library of population genetic models AU - Adrion, Jeffrey R AU - Cole, Christopher B AU - Dukler, Noah AU - Galloway, Jared G AU - Gladstein, Ariella L AU - Gower, Graham AU - Kyriazis, Christopher C AU - Ragsdale, Aaron P AU - Tsambos, Georgia AU - Baumdicker, Franz AU - Carlson, Jedidiah AU - Cartwright, Reed A AU - Durvasula, Arun AU - Gronau, Ilan AU - Kim, Bernard Y AU - McKenzie, Patrick AU - Messer, Philipp W AU - Noskova, Ekaterina AU - Ortega-Del Vecchyo, Diego AU - Racimo, Fernando AU - Struck, Travis J AU - Gravel, Simon AU - Gutenkunst, Ryan N AU - Lohmueller, Kirk E AU - Ralph, Peter L AU - Schrider, Daniel R AU - Siepel, Adam AU - Kelleher, Jerome AU - Kern, Andrew D A2 - Coop, Graham A2 - Wittkopp, Patricia J A2 - Novembre, John A2 - Sethuraman, Arun A2 - Mathieson, Sara VL - 9 PY - 2020 DA - 2020/06/23 SP - e54967 C1 - eLife 2020;9:e54967 DO - 10.7554/eLife.54967 UR - https://doi.org/10.7554/eLife.54967 AB - The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource. KW - simulation KW - reproducibility KW - open source JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -