Efficient ancestry and mutation simulation with msprime 1.0

Abstract Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce<jats:monospace>msprime</jats:monospace>version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and<jats:monospace>tskit</jats:monospace>library. We summarise<jats:monospace>msprime</jats:monospace>’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement..

Medienart:

Preprint

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

bioRxiv.org - (2023) vom: 08. Nov. Zur Gesamtaufnahme - year:2023

Sprache:

Englisch

Beteiligte Personen:

Baumdicker, Franz [VerfasserIn]
Bisschop, Gertjan [VerfasserIn]
Goldstein, Daniel [VerfasserIn]
Gower, Graham [VerfasserIn]
Ragsdale, Aaron P. [VerfasserIn]
Tsambos, Georgia [VerfasserIn]
Zhu, Sha [VerfasserIn]
Eldon, Bjarki [VerfasserIn]
Ellerman, E. Castedo [VerfasserIn]
Galloway, Jared G. [VerfasserIn]
Gladstein, Ariella L. [VerfasserIn]
Gorjanc, Gregor [VerfasserIn]
Guo, Bing [VerfasserIn]
Jeffery, Ben [VerfasserIn]
Kretzschmar, Warren W. [VerfasserIn]
Lohse, Konrad [VerfasserIn]
Matschiner, Michael [VerfasserIn]
Nelson, Dominic [VerfasserIn]
Pope, Nathaniel S. [VerfasserIn]
Quinto-Cortés, Consuelo D. [VerfasserIn]
Rodrigues, Murillo F. [VerfasserIn]
Saunack, Kumar [VerfasserIn]
Sellinger, Thibaut [VerfasserIn]
Thornton, Kevin [VerfasserIn]
van Kemenade, Hugo [VerfasserIn]
Wohns, Anthony W. [VerfasserIn]
Wong, Yan [VerfasserIn]
Gravel, Simon [VerfasserIn]
Kern, Andrew D. [VerfasserIn]
Koskela, Jere [VerfasserIn]
Ralph, Peter L. [VerfasserIn]
Kelleher, Jerome [VerfasserIn]

Links:

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Themen:

570
Biology

doi:

10.1101/2021.08.31.457499

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI032496664