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Efficient pedigree recording for fast population genetics simulation

View ORCID ProfileJerome Kelleher, View ORCID ProfileKevin R. Thornton, View ORCID ProfileJaime Ashander, View ORCID ProfilePeter L. Ralph
doi: https://doi.org/10.1101/248500
Jerome Kelleher
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Kevin R. Thornton
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Jaime Ashander
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Peter L. Ralph
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Abstract

In this paper we describe how to efficiently record the entire genetic history of a population during a forwards-time, individual-based population genetics simulation. This dramatically reduces the computational burden of tracking individual genomes by simulating only those loci that may affect reproduction (those having non-neutral variants), and recording history as a succinct tree sequence as introduced in the software package msprime, on which neutral mutations can be quickly placed afterwards. We implement the method in two popular forwards-time simulation frameworks, which speeds up large, whole-genome simulations by one to two orders of magnitude. In addition to speed, the method 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 (and its’ history) rather than only a subset. (3) A simulation can easily be initialized with a more efficient coalescent simulation of deep history. To make these possible, we introduce the msprime Tables API, which allows for the efficient interchange of tree sequences between modular program components, and provide an algorithm to quickly simplify a tree sequence by removing history irrelevant to a given set of genomes.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted January 16, 2018.
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Efficient pedigree recording for fast population genetics simulation
Jerome Kelleher, Kevin R. Thornton, Jaime Ashander, Peter L. Ralph
bioRxiv 248500; doi: https://doi.org/10.1101/248500
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Efficient pedigree recording for fast population genetics simulation
Jerome Kelleher, Kevin R. Thornton, Jaime Ashander, Peter L. Ralph
bioRxiv 248500; doi: https://doi.org/10.1101/248500

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