Evidence map›Paper›PMID 36173327›Full record

ArticleGenetics2022

Demes: a standard format for demographic models.

Graham Gower, Aaron P Ragsdale, Gertjan Bisschop, Ryan N Gutenkunst, Matthew Hartfield, Ekaterina Noskova, Stephan Schiffels, Travis J Struck, Jerome Kelleher, Kevin R Thornton

Abstract read
In one paragraph

Article in Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

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  10. Neural posterior estimation for population genetics.bioRxiv : the preprint server for biology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Graham GowerSection for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, 1350 Copenhagen K, Denmark.ORCID 0000-0002-6197-3872
Aaron P RagsdaleDepartment of Integrative Biology, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0003-0715-3432
Gertjan BisschopInstitute of Ecology and Evolution, The University of Edinburgh, Edinburgh EH9 3FL, UK.ORCID 0000-0001-8327-0142
Ryan N GutenkunstDepartment of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA.ORCID 0000-0002-8659-0579
Matthew HartfieldInstitute of Ecology and Evolution, The University of Edinburgh, Edinburgh EH9 3FL, UK.ORCID 0000-0001-6941-0647
Ekaterina NoskovaComputer Technologies Laboratory, ITMO University, 197101 Saint-Petersburg, Russia.ORCID 0000-0003-1168-0497
Stephan SchiffelsMax Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany.ORCID 0000-0002-1017-9150
Travis J StruckDepartment of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA.ORCID 0000-0001-7161-5107
Jerome KelleherBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.ORCID 0000-0002-7894-5253
Kevin R ThorntonDepartment of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA.ORCID 0000-0003-0743-4445

Funding

Joint inferences of natural selection between sites and populationsR01GM127348 · NIGMS · UNIVERSITY OF ARIZONA · PI GUTENKUNST, RYAN · 2019 to 2023
$1.7M
NIGMS NIH HHS R01 GM127348
6 · The paper itself

Abstract

Understanding the demographic history of populations is a key goal in population genetics, and with improving methods and data, ever more complex models are being proposed and tested. Demographic models of current interest typically consist of a set of discrete populations, their sizes and growth rates, and continuous and pulse migrations between those populations over a number of epochs, which can require dozens of parameters to fully describe. There is currently no standard format to define such models, significantly hampering progress in the field. In particular, the important task of translating the model descriptions in published work into input suitable for population genetic simulators is labor intensive and error prone. We propose the Demes data model and file format, built on widely used technologies, to alleviate these issues. Demes provide a well-defined and unambiguous model of populations and their properties that is straightforward to implement in software, and a text file format that is designed for simplicity and clarity. We provide thoroughly tested implementations of Demes parsers in multiple languages including Python and C, and showcase initial support in several simulators and inference methods. An introduction to the file format and a detailed specification are available at https://popsim-consortium.github.io/demes-spec-docs/.

Indexed as

Genetics, PopulationSoftwareDemographydemographic modelsinferencesimulation

Identifiers

PMID36173327
PMCPMC9630982

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.