Efficient pedigree recording for fast population genetics simulation
In this paper we describe how to efficiently record the entire genetic history of a population in forwards-time, individual-based population genetics simulations with arbitrary breeding models, population structure and demography. This approach dramatically reduces the computational burden of tracki...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Public Library of Science
2018
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| _version_ | 1797068434476892160 |
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| author | Kelleher, J Thornton, K Ashander, J Ralph, P |
| author_facet | Kelleher, J Thornton, K Ashander, J Ralph, P |
| author_sort | Kelleher, J |
| collection | OXFORD |
| description | In this paper we describe how to efficiently record the entire genetic history of a population in forwards-time, individual-based population genetics simulations with arbitrary breeding models, population structure and demography. This approach dramatically reduces the computational burden of tracking individual genomes by allowing us to simulate only those loci that may affect reproduction (those having non-neutral variants). The genetic history of the population is recorded as a succinct tree sequence as introduced in the software package msprime, on which neutral mutations can be quickly placed afterwards. Recording the results of each breeding event requires storage that grows linearly with time, but there is a great deal of redundancy in this information. We solve this storage problem by providing an algorithm to quickly 'simplify' a tree sequence by removing this irrelevant history for a given set of genomes. By periodically simplifying the history with respect to the extant population, we show that the total storage space required is modest and overall large efficiency gains can be made over classical forward-time simulations. We implement a general-purpose framework for recording and simplifying genealogical data, which can be used to make simulations of any population model more efficient. We modify two popular forwards-time simulation frameworks to use this new approach and observe efficiency gains in large, whole-genome simulations of one to two orders of magnitude. In addition to speed, our method for recording pedigrees has several advantages: (1) All marginal genealogies of the simulated individuals are recorded, rather than just genotypes. (2) A population of N individuals with M polymorphic sites can be stored in O(N log N + M) space, making it feasible to store a simulation's entire final generation as well as its history. (3) A simulation can easily be initialized with a more efficient coalescent simulation of deep history. The software for recording and processing tree sequences is named tskit. |
| first_indexed | 2024-03-06T22:10:44Z |
| format | Journal article |
| id | oxford-uuid:51b6a415-fe41-4375-bb74-d2a5338e455a |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T22:10:44Z |
| publishDate | 2018 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:51b6a415-fe41-4375-bb74-d2a5338e455a2022-03-26T16:21:15ZEfficient pedigree recording for fast population genetics simulationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:51b6a415-fe41-4375-bb74-d2a5338e455aEnglishSymplectic Elements at OxfordPublic Library of Science2018Kelleher, JThornton, KAshander, JRalph, PIn this paper we describe how to efficiently record the entire genetic history of a population in forwards-time, individual-based population genetics simulations with arbitrary breeding models, population structure and demography. This approach dramatically reduces the computational burden of tracking individual genomes by allowing us to simulate only those loci that may affect reproduction (those having non-neutral variants). The genetic history of the population is recorded as a succinct tree sequence as introduced in the software package msprime, on which neutral mutations can be quickly placed afterwards. Recording the results of each breeding event requires storage that grows linearly with time, but there is a great deal of redundancy in this information. We solve this storage problem by providing an algorithm to quickly 'simplify' a tree sequence by removing this irrelevant history for a given set of genomes. By periodically simplifying the history with respect to the extant population, we show that the total storage space required is modest and overall large efficiency gains can be made over classical forward-time simulations. We implement a general-purpose framework for recording and simplifying genealogical data, which can be used to make simulations of any population model more efficient. We modify two popular forwards-time simulation frameworks to use this new approach and observe efficiency gains in large, whole-genome simulations of one to two orders of magnitude. In addition to speed, our method for recording pedigrees has several advantages: (1) All marginal genealogies of the simulated individuals are recorded, rather than just genotypes. (2) A population of N individuals with M polymorphic sites can be stored in O(N log N + M) space, making it feasible to store a simulation's entire final generation as well as its history. (3) A simulation can easily be initialized with a more efficient coalescent simulation of deep history. The software for recording and processing tree sequences is named tskit. |
| spellingShingle | Kelleher, J Thornton, K Ashander, J Ralph, P Efficient pedigree recording for fast population genetics simulation |
| title | Efficient pedigree recording for fast population genetics simulation |
| title_full | Efficient pedigree recording for fast population genetics simulation |
| title_fullStr | Efficient pedigree recording for fast population genetics simulation |
| title_full_unstemmed | Efficient pedigree recording for fast population genetics simulation |
| title_short | Efficient pedigree recording for fast population genetics simulation |
| title_sort | efficient pedigree recording for fast population genetics simulation |
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