Author summary Sexually reproducing organisms are related to the others in their species by the complex web of parent-offspring relationships that constitute the pedigree. In this paper, we describe a way to record all of these relationships, as well as how genetic material is passed down through the pedigree, during a forwards-time population genetic simulation. To make effective use of this information, we describe both efficient storage methods for this embellished pedigree as well as a way to remove all information that is irrelevant to the genetic history of a given set of individuals, which dramatically reduces the required amount of storage space. Storing this information allows us to produce whole-genome sequence from simulations of large populations in which we have not explicitly recorded new genomic mutations; we find that this results in computational run times of up to 50 times faster than simulations forced to explicitly carry along that information.
Description
Efficient pedigree recording for fast population genetics simulation
%0 Journal Article
%1 kelleher2018efficient
%A Kelleher, Jerome
%A Thornton, Kevin R.
%A Ashander, Jaime
%A Ralph, Peter L.
%D 2018
%I Public Library of Science
%J PLOS Computational Biology
%K ARG methods myown simulation software tree_sequence
%N 11
%P 1-21
%R 10.1371/journal.pcbi.1006581
%T Efficient pedigree recording for fast population genetics simulation
%U https://doi.org/10.1371/journal.pcbi.1006581
%V 14
%X Author summary Sexually reproducing organisms are related to the others in their species by the complex web of parent-offspring relationships that constitute the pedigree. In this paper, we describe a way to record all of these relationships, as well as how genetic material is passed down through the pedigree, during a forwards-time population genetic simulation. To make effective use of this information, we describe both efficient storage methods for this embellished pedigree as well as a way to remove all information that is irrelevant to the genetic history of a given set of individuals, which dramatically reduces the required amount of storage space. Storing this information allows us to produce whole-genome sequence from simulations of large populations in which we have not explicitly recorded new genomic mutations; we find that this results in computational run times of up to 50 times faster than simulations forced to explicitly carry along that information.
@article{kelleher2018efficient,
abstract = {Author summary Sexually reproducing organisms are related to the others in their species by the complex web of parent-offspring relationships that constitute the pedigree. In this paper, we describe a way to record all of these relationships, as well as how genetic material is passed down through the pedigree, during a forwards-time population genetic simulation. To make effective use of this information, we describe both efficient storage methods for this embellished pedigree as well as a way to remove all information that is irrelevant to the genetic history of a given set of individuals, which dramatically reduces the required amount of storage space. Storing this information allows us to produce whole-genome sequence from simulations of large populations in which we have not explicitly recorded new genomic mutations; we find that this results in computational run times of up to 50 times faster than simulations forced to explicitly carry along that information.},
added-at = {2018-12-09T17:30:18.000+0100},
author = {Kelleher, Jerome and Thornton, Kevin R. and Ashander, Jaime and Ralph, Peter L.},
biburl = {https://www.bibsonomy.org/bibtex/2a4f12f0bb2d13faee628fec0fc2679b8/peter.ralph},
description = {Efficient pedigree recording for fast population genetics simulation},
doi = {10.1371/journal.pcbi.1006581},
interhash = {b855fb1dfdb8542b91b86dff2be80c63},
intrahash = {a4f12f0bb2d13faee628fec0fc2679b8},
journal = {PLOS Computational Biology},
keywords = {ARG methods myown simulation software tree_sequence},
month = {11},
number = 11,
pages = {1-21},
publisher = {Public Library of Science},
timestamp = {2018-12-09T17:30:18.000+0100},
title = {Efficient pedigree recording for fast population genetics simulation},
url = {https://doi.org/10.1371/journal.pcbi.1006581},
volume = 14,
year = 2018
}