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Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations
Author
Lauterbur, M.E.Cavassim, M.I.A.
Gladstein, A.L.
Gower, G.
Pope, N.S.
Tsambos, G.
Adrion, J.
Belsare, S.
Biddanda, A.
Caudill, V.
Cury, J.
Echevarria, I.
Haller, B.C.
Hasan, A.R.
Huang, X.
Iasi, L.N.M.
Noskova, E.
Obsteter, J.
Pavinato, V.A.C.
Pearson, A.
Peede, D.
Perez, M.F.
Rodrigues, M.F.
Smith, C.C.R.
Spence, J.P.
Teterina, A.
Tittes, S.
Unneberg, P.
Vazquez, J.M.
Waples, R.K.
Wohns, A.W.
Wong, Y.
Baumdicker, F.
Cartwright, R.A.
Gorjanc, G.
Gutenkunst, R.N.
Kelleher, J.
Kern, A.D.
Ragsdale, A.P.
Ralph, P.L.
Schrider, D.R.
Gronau, I.
Affiliation
Department of Molecular and Cellular Biology, University of ArizonaDepartment of Ecology and Evolutionary Biology, University of Arizona
Issue Date
2023-06-21
Metadata
Show full item recordPublisher
eLife Sciences Publications LtdCitation
M Elise LauterburMaria Izabel A CavassimAriella L GladsteinGraham GowerNathaniel S PopeGeorgia TsambosJeffrey AdrionSaurabh BelsareArjun BiddandaVictoria CaudillJean CuryIgnacio EchevarriaBenjamin C HallerAhmed R HasanXin HuangLeonardo Nicola Martin IasiEkaterina NoskovaJana ObsteterVitor Antonio Correa PavinatoAlice PearsonDavid PeedeManolo F PerezMurillo F RodriguesChris CR SmithJeffrey P SpenceAnastasia TeterinaSilas TittesPer UnnebergJuan Manuel VazquezRyan K WaplesAnthony Wilder WohnsYan WongFranz BaumdickerReed A CartwrightGregor GorjancRyan N GutenkunstJerome KelleherAndrew D KernAaron P RagsdalePeter L RalphDaniel R SchriderIlan Gronau (2023) Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations eLife 12:RP84874.Journal
eLifeRights
© Lauterbur et al. This article is distributed under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
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. © Lauterbur et al.Note
Open access journalISSN
2050-084XPubMed ID
37342968Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.7554/eLife.84874
Scopus Count
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Except where otherwise noted, this item's license is described as © Lauterbur et al. This article is distributed under the terms of the Creative Commons Attribution License.