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 duplication of effort and the possibility for error. 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 standard catalog of published simulation models from a wide range of organisms and supports multiple simulation engine backends. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage an even broader community of developers to contribute to this growing resource.
- Population genetics
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)
- Immunology and Microbiology(all)
- Pharmacology, Toxicology and Pharmaceutics(all)