1. Computational and Systems Biology
  2. Evolutionary Biology

A community-maintained standard library of population genetic models

  1. Jeffrey R Adrion
  2. Christopher B Cole
  3. Noah Dukler
  4. Jared G Galloway
  5. Ariella L Gladstein
  6. Graham Gower
  7. Christopher C Kyriazis
  8. Aaron P Ragsdale
  9. Georgia Tsambos
  10. Franz Baumdicker
  11. Jedidiah Carlson
  12. Reed A Cartwright
  13. Arun Durvasula
  14. Ilan Gronau
  15. Bernard Y Kim
  16. Patrick McKenzie
  17. Philipp W Messer
  18. Ekaterina Noskova
  19. Diego Ortega Del Vecchyo
  20. Fernando Racimo
  21. Travis J Struck
  22. Simon Gravel
  23. Ryan N Gutenkunst
  24. Kirk E Lohmueller
  25. Peter L Ralph
  26. Daniel R Schrider
  27. Adam Siepel
  28. Jerome Kelleher  Is a corresponding author
  29. Andrew D Kern  Is a corresponding author
  1. University of Oregon, United States
  2. University of Oxford, United Kingdom
  3. Cold Spring Harbor Laboratory, United States
  4. University of North Carolina at Chapel Hill, United States
  5. University of Copenhagen, Denmark
  6. University of California, Los Angeles, United States
  7. McGill University, Canada
  8. University of Melbourne, Australia
  9. University of Freiburg, Germany
  10. University of Washington, United States
  11. Arizona State University, United States
  12. IDC Herzliya, Israel
  13. Stanford University, United States
  14. Columbia University, United States
  15. Cornell University, United States
  16. ITMO University, Russian Federation
  17. National Autonomous University of Mexico, Mexico
  18. University of Arizona, United States
https://doi.org/10.7554/eLife.54967
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Cite this article
  1. Jeffrey R Adrion
  2. Christopher B Cole
  3. Noah Dukler
  4. Jared G Galloway
  5. Ariella L Gladstein
  6. Graham Gower
  7. Christopher C Kyriazis
  8. Aaron P Ragsdale
  9. Georgia Tsambos
  10. Franz Baumdicker
  11. Jedidiah Carlson
  12. Reed A Cartwright
  13. Arun Durvasula
  14. Ilan Gronau
  15. Bernard Y Kim
  16. Patrick McKenzie
  17. Philipp W Messer
  18. Ekaterina Noskova
  19. Diego Ortega Del Vecchyo
  20. Fernando Racimo
  21. Travis J Struck
  22. Simon Gravel
  23. Ryan N Gutenkunst
  24. Kirk E Lohmueller
  25. Peter L Ralph
  26. Daniel R Schrider
  27. Adam Siepel
  28. Jerome Kelleher
  29. Andrew D Kern
(2020)
A community-maintained standard library of population genetic models
eLife 9:e54967.
https://doi.org/10.7554/eLife.54967
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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. 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.

Data availability

All resources are available from https://github.com/popsim-consortium/stdpopsim

Article and author information

Author details

  1. Jeffrey R Adrion

    Department of Biology, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.

  2. Christopher B Cole

    Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6733-633X

  3. Noah Dukler

    Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8739-8052

  4. Jared G Galloway

    Department of Biology and Institute of Ecology and Evolution, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.

  5. Ariella L Gladstein

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    No competing interests declared.

  6. Graham Gower

    Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6197-3872

  7. Christopher C Kyriazis

    Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.

  8. Aaron P Ragsdale

    Human Genetics, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0715-3432

  9. Georgia Tsambos

    Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7001-2275

  10. Franz Baumdicker

    Department of Mathematical Stochastics, University of Freiburg, Freiburg, Germany
    Competing interests
    No competing interests declared.

  11. Jedidiah Carlson

    Department of Genome Sciences, University of Washington, Seattle, United States
    Competing interests
    No competing interests declared.

  12. Reed A Cartwright

    The Biodesign Institute and The School of Life Sciences, Arizona State University, Tempe, United States
    Competing interests
    No competing interests declared.

  13. Arun Durvasula

    Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0631-3238

  14. Ilan Gronau

    IDC Herzliya, Herzliya, Israel
    Competing interests
    No competing interests declared.

  15. Bernard Y Kim

    Department of Biology, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.

  16. Patrick McKenzie

    Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, United States
    Competing interests
    No competing interests declared.

  17. Philipp W Messer

    Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, United States
    Competing interests
    Philipp W Messer, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8453-9377

  18. Ekaterina Noskova

    Computer Technologies Laboratory, ITMO University, Saint Petersburg, Russian Federation
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1168-0497

  19. Diego Ortega Del Vecchyo

    International Laboratory for Human Genome Research, National Autonomous University of Mexico, Juriquilla, Mexico
    Competing interests
    No competing interests declared.

  20. Fernando Racimo

    Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5025-2607

  21. Travis J Struck

    Molecular and Cellular Biology, University of Arizona, Tucson, United States
    Competing interests
    No competing interests declared.

  22. Simon Gravel

    Human Genetics, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.

  23. Ryan N Gutenkunst

    Molecular and Cellular Biology, University of Arizona, Tucson, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8659-0579

  24. Kirk E Lohmueller

    Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3874-369X

  25. Peter L Ralph

    Institute of Ecology and Evolution, University of Oregon, Eugene, United States
    Competing interests
    No competing interests declared.

  26. Daniel R Schrider

    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5249-4151

  27. Adam Siepel

    Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    Competing interests
    No competing interests declared.

  28. Jerome Kelleher

    Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
    For correspondence
    jerome.kelleher@bdi.ox.ac.uk
    Competing interests
    No competing interests declared.

  29. Andrew D Kern

    Institute of Ecology and Evolution, University of Oregon, Eugene, United States
    For correspondence
    adkern@uoregon.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4381-4680

Funding

National Institute of General Medical Sciences (R35GM119856)

  • Christopher C Kyriazis
  • Kirk E Lohmueller

National Institute of General Medical Sciences (R01GM117241)

  • Jeffrey R Adrion
  • Andrew D Kern

National Institute of General Medical Sciences (R01GM127348)

  • Travis J Struck
  • Ryan N Gutenkunst

National Institute of General Medical Sciences (R00HG008696)

  • Ariella L Gladstein
  • Daniel R Schrider

National Institute of General Medical Sciences (R35GM127070)

  • Noah Dukler
  • Adam Siepel

National Human Genome Research Institute (R01HG010346)

  • Noah Dukler
  • Adam Siepel

Villum Fonden (00025300)

  • Graham Gower
  • Fernando Racimo

UC MEXUS-CONACYT

  • Diego Ortega Del Vecchyo

Robertson Foundation

  • Jerome Kelleher

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Adrion et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Jeffrey R Adrion
  2. Christopher B Cole
  3. Noah Dukler
  4. Jared G Galloway
  5. Ariella L Gladstein
  6. Graham Gower
  7. Christopher C Kyriazis
  8. Aaron P Ragsdale
  9. Georgia Tsambos
  10. Franz Baumdicker
  11. Jedidiah Carlson
  12. Reed A Cartwright
  13. Arun Durvasula
  14. Ilan Gronau
  15. Bernard Y Kim
  16. Patrick McKenzie
  17. Philipp W Messer
  18. Ekaterina Noskova
  19. Diego Ortega Del Vecchyo
  20. Fernando Racimo
  21. Travis J Struck
  22. Simon Gravel
  23. Ryan N Gutenkunst
  24. Kirk E Lohmueller
  25. Peter L Ralph
  26. Daniel R Schrider
  27. Adam Siepel
  28. Jerome Kelleher
  29. Andrew D Kern
(2020)
A community-maintained standard library of population genetic models
eLife 9:e54967.
https://doi.org/10.7554/eLife.54967

Share this article

https://doi.org/10.7554/eLife.54967

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Research organism

Further reading

    1. Genetics and Genomics

    Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

    M Elise Lauterbur, Maria Izabel A Cavassim ... Ilan Gronau
    Research Advance

    Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.