Demes: a standard format for demographic models
Research output: Contribution to journal › Journal article › Research › peer-review
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Demes : a standard format for demographic models. / Gower, Graham; Ragsdale, Aaron P.; Bisschop, Gertjan; Gutenkunst, Ryan N.; Hartfield, Matthew; Noskova, Ekaterina; Schiffels, Stephan; Struck, Travis J.; Kelleher, Jerome; Thornton, Kevin R.
In: Genetics, Vol. 222, No. 3, iyac131, 2022.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Demes
T2 - a standard format for demographic models
AU - Gower, Graham
AU - Ragsdale, Aaron P.
AU - Bisschop, Gertjan
AU - Gutenkunst, Ryan N.
AU - Hartfield, Matthew
AU - Noskova, Ekaterina
AU - Schiffels, Stephan
AU - Struck, Travis J.
AU - Kelleher, Jerome
AU - Thornton, Kevin R.
PY - 2022
Y1 - 2022
N2 - 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 .
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 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 .
KW - demographic models
KW - inference
KW - simulation
KW - POPULATION GENETIC SIMULATION
KW - COALESCENT SIMULATION
KW - SELECTION
KW - EVOLUTIONARY
KW - HISTORY
KW - COMPUTATION
KW - DIVERSITY
KW - SEQUENCES
KW - INFERENCE
KW - SAMPLES
U2 - 10.1093/genetics/iyac131
DO - 10.1093/genetics/iyac131
M3 - Journal article
C2 - 36173327
VL - 222
JO - Genetics
JF - Genetics
SN - 1943-2631
IS - 3
M1 - iyac131
ER -
ID: 322868710