Efficient ancestry and mutation simulation with msprime 1.0

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

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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 msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and tskit library. We summarise msprime’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.
Original languageEnglish
JournalGenetics
Early online date13 Dec 2021
DOIs
Publication statusE-pub ahead of print - 13 Dec 2021

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