Adrion, JR, Cole, C. B., Dukler, N., Galloway, JG, Gladstein, AL, Gower, G, Kyriazis, CC, Ragsdale, AP, Tsambos, G, Baumdicker, F, Carlson, J., Cartwright, R. A., Durvasula, A, Gronau, I., Kim, BY, McKenzie, P, Messer, PW, Noskova, E, Ortega-Del Vecchyo, D., Racimo, F, Struck, TJ, Gravel, S, Gutenkunst, R. N., Lohmueller, K. E., Ralph, PL, Schrider, D. R., Siepel, A., Kelleher, J. E., Kern, A. D. (June 2020) A Community-Maintained Standard Library of Population Genetic Models. Elife, 9. ISSN 2050-084X (Electronic)2050-084X (Linking)
Abstract
The explosion in population genomic data demands ever more complex modes of analysis, and increasingly these analyses depend on sophisticated simulations. Re-cent 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.
| Item Type: | Paper |
|---|---|
| Subjects: | organism description > plant > Arabidopsis bioinformatics organism description > animal > insect > Drosophila bioinformatics > genomics and proteomics > genetics & nucleic acid processing bioinformatics > genomics and proteomics organism description > animal organism description > bacteria organism description > bacteria > escherichia coli organism description > animal > insect organism description > plant bioinformatics > genomics and proteomics > genetics & nucleic acid processing > population genetics |
| CSHL Authors: | |
| Communities: | CSHL labs > Siepel lab CSHL Cancer Center Program > Cancer Genetics and Genomics Program |
| Depositing User: | Matthew Dunn |
| Date: | 23 June 2020 |
| Date Deposited: | 06 Jul 2020 19:01 |
| Last Modified: | 26 Jan 2024 17:08 |
| PMCID: | PMC7438115 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/39511 |
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