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A community-maintained standard library of population genetic models

View ORCID ProfileJeffrey R. Adrion, View ORCID ProfileChristopher B. Cole, View ORCID ProfileNoah Dukler, Jared G. Galloway, View ORCID ProfileAriella L. Gladstein, View ORCID ProfileGraham Gower, View ORCID ProfileChristopher C. Kyriazis, View ORCID ProfileAaron P. Ragsdale, Georgia Tsambos, Franz Baumdicker, View ORCID ProfileJedidiah Carlson, View ORCID ProfileReed A. Cartwright, View ORCID ProfileArun Durvasula, View ORCID ProfileIlan Gronau, Bernard Y. Kim, View ORCID ProfilePatrick McKenzie, View ORCID ProfilePhilipp W. Messer, View ORCID ProfileEkaterina Noskova, View ORCID ProfileDiego Ortega-Del Vecchyo, Fernando Racimo, View ORCID ProfileTravis J. Struck, View ORCID ProfileSimon Gravel, View ORCID ProfileRyan N. Gutenkunst, Kirk E. Lohmueller, View ORCID ProfilePeter L. Ralph, View ORCID ProfileDaniel R. Schrider, View ORCID ProfileAdam Siepel, View ORCID ProfileJerome Kelleher, View ORCID ProfileAndrew D. Kern
doi: https://doi.org/10.1101/2019.12.20.885129
Jeffrey R. Adrion
1Department of Biology and Institute of Ecology and Evolution, University of Oregon
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Christopher B. Cole
2Wellcome Trust Centre for Human Genetics, University of Oxford
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Noah Dukler
3Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory
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Jared G. Galloway
1Department of Biology and Institute of Ecology and Evolution, University of Oregon
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Ariella L. Gladstein
4Department of Genetics, University of North Carolina at Chapel Hill
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Graham Gower
5Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen
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Christopher C. Kyriazis
6Department of Ecology and Evolutionary Biology, University of California, Los Angeles
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Aaron P. Ragsdale
7Department of Human Genetics, McGill University
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Georgia Tsambos
8Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne
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Franz Baumdicker
9Department of Mathematical Stochastics, University of Freiburg
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Jedidiah Carlson
10Department of Genome Sciences, University of Washington
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Reed A. Cartwright
11The Biodesign Institute and The School of Life Sciences, Arizona State University
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Arun Durvasula
12Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles
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Ilan Gronau
13The Efi Arazi School of Computer Science, The Herzliya Interdisciplinary Center, Israel
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Bernard Y. Kim
14Department of Biology, Stanford University
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Patrick McKenzie
15Department of Ecology, Evolution, and Environmental Biology, Columbia University
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Philipp W. Messer
16Department of Computational Biology, Cornell University
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Ekaterina Noskova
17Computer Technologies Laboratory, ITMO University
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Diego Ortega-Del Vecchyo
18International Laboratory for Human Genome Research, National Autonomous University of Mexico
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Fernando Racimo
5Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen
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Travis J. Struck
19Department of Molecular and Cellular Biology, University of Arizona
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Simon Gravel
7Department of Human Genetics, McGill University
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Ryan N. Gutenkunst
19Department of Molecular and Cellular Biology, University of Arizona
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Kirk E. Lohmueller
6Department of Ecology and Evolutionary Biology, University of California, Los Angeles
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Peter L. Ralph
1Department of Biology and Institute of Ecology and Evolution, University of Oregon
20Department of Mathematics, University of Oregon
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Daniel R. Schrider
4Department of Genetics, University of North Carolina at Chapel Hill
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Adam Siepel
3Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory
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Jerome Kelleher
21Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford
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  • For correspondence: adkern@uoregon.edu
Andrew D. Kern
1Department of Biology and Institute of Ecology and Evolution, University of Oregon
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  • For correspondence: adkern@uoregon.edu
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Abstract

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.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵⋆ Denotes shared first authorship, listed alphabetically,

  • ↵† Denotes shared senior authorship, listed alphabetically,

  • https://github.com/popsim-consortium/stdpopsim

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 17, 2020.
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A community-maintained standard library of population genetic models
Jeffrey R. Adrion, Christopher B. Cole, Noah Dukler, Jared G. Galloway, Ariella L. Gladstein, Graham Gower, Christopher C. Kyriazis, Aaron P. Ragsdale, Georgia Tsambos, Franz Baumdicker, Jedidiah Carlson, Reed A. Cartwright, Arun Durvasula, Ilan Gronau, Bernard Y. Kim, Patrick McKenzie, Philipp W. Messer, Ekaterina Noskova, Diego Ortega-Del Vecchyo, Fernando Racimo, Travis J. Struck, Simon Gravel, Ryan N. Gutenkunst, Kirk E. Lohmueller, Peter L. Ralph, Daniel R. Schrider, Adam Siepel, Jerome Kelleher, Andrew D. Kern
bioRxiv 2019.12.20.885129; doi: https://doi.org/10.1101/2019.12.20.885129
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A community-maintained standard library of population genetic models
Jeffrey R. Adrion, Christopher B. Cole, Noah Dukler, Jared G. Galloway, Ariella L. Gladstein, Graham Gower, Christopher C. Kyriazis, Aaron P. Ragsdale, Georgia Tsambos, Franz Baumdicker, Jedidiah Carlson, Reed A. Cartwright, Arun Durvasula, Ilan Gronau, Bernard Y. Kim, Patrick McKenzie, Philipp W. Messer, Ekaterina Noskova, Diego Ortega-Del Vecchyo, Fernando Racimo, Travis J. Struck, Simon Gravel, Ryan N. Gutenkunst, Kirk E. Lohmueller, Peter L. Ralph, Daniel R. Schrider, Adam Siepel, Jerome Kelleher, Andrew D. Kern
bioRxiv 2019.12.20.885129; doi: https://doi.org/10.1101/2019.12.20.885129

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