%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 }