Demes: a standard format for demographic models

Author:

Gower Graham1ORCID,Ragsdale Aaron P2ORCID,Bisschop Gertjan3ORCID,Gutenkunst Ryan N4ORCID,Hartfield Matthew3ORCID,Noskova Ekaterina5ORCID,Schiffels Stephan6ORCID,Struck Travis J4ORCID,Kelleher Jerome7ORCID,Thornton Kevin R8ORCID

Affiliation:

1. Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen , 1350 Copenhagen K, Denmark

2. Department of Integrative Biology, University of Wisconsin–Madison , Madison, WI 53706, USA

3. Institute of Ecology and Evolution, The University of Edinburgh , Edinburgh EH9 3FL, UK

4. Department of Molecular and Cellular Biology, University of Arizona , Tucson, AZ 85721, USA

5. Computer Technologies Laboratory, ITMO University , 197101 Saint-Petersburg, Russia

6. Max Planck Institute for Evolutionary Anthropology , 04103 Leipzig, Germany

7. Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford , Oxford OX3 7LF, UK

8. Department of Ecology and Evolutionary Biology, University of California , Irvine, CA 92697, USA

Abstract

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/.

Funder

Villum Fonden Young Investigator award to Fernando Racimo

National Institute of General Medical Sciences of the National Institutes of Health

Natural Environment Research Council Independent Research Fellowship

Robertson Foundation

European Research Council under the European Union’s Horizon 2020 research and innovation program

European Research Council (ModelGenomLand

Publisher

Oxford University Press (OUP)

Subject

Genetics

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