RT Journal Article
SR Electronic
T1 Demes: a standard format for demographic models
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.05.31.494112
DO 10.1101/2022.05.31.494112
A1 Graham Gower
A1 Aaron P. Ragsdale
A1 Ryan N. Gutenkunst
A1 Matthew Hartfield
A1 Ekaterina Noskova
A1 Travis J. Struck
A1 Jerome Kelleher
A1 Kevin R. Thornton
YR 2022
UL http://biorxiv.org/content/early/2022/06/01/2022.05.31.494112.abstract
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.