Demes: A standard format for demographic models

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

Research output: Contribution to journalArticlepeer-review

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/.

Original languageEnglish
Article numberiyac131
Number of pages18
JournalGenetics
Volume222
Issue number3
Early online date29 Sep 2022
DOIs
Publication statusPublished - 1 Nov 2022

Keywords

  • demographic models
  • inference
  • simulation

Fingerprint

Dive into the research topics of 'Demes: A standard format for demographic models'. Together they form a unique fingerprint.

Cite this