PT  - JOURNAL ARTICLE
AU  - Graham Gower
AU  - Aaron P. Ragsdale
AU  - Ryan N. Gutenkunst
AU  - Matthew Hartfield
AU  - Ekaterina Noskova
AU  - Travis J. Struck
AU  - Jerome Kelleher
AU  - Kevin R. Thornton
TI  - Demes: a standard format for demographic models
AID  - 10.1101/2022.05.31.494112
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.05.31.494112
4099  - http://biorxiv.org/content/early/2022/06/01/2022.05.31.494112.short
4100  - http://biorxiv.org/content/early/2022/06/01/2022.05.31.494112.full
AB  - 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 provides 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 Python and C, and showcase initial support in several simulators and inference methods.Competing Interest StatementThe authors have declared no competing interest.