Efficient ancestry and mutation simulation with msprime 1.0
Baumdicker FPapers in this archive, Bisschop GPapers in this archive, Goldstein DPapers in this archive, Gower GPapers in this archive, Ragsdale APPapers in this archive, Tsambos GPapers in this archive, Zhu SPapers in this archive, Eldon BPapers in this archive, Ellerman ECPapers in this archive, Galloway JGPapers in this archive, Gladstein ALPapers in this archive, Gorjanc GPapers in this archive, Guo BPapers in this archive, Jeffery BPapers in this archive, Kretzschumar WWPapers in this archive, Lohse KPapers in this archive, Matschiner MPapers in this archive, Nelson DPapers in this archive, Pope NSPapers in this archive, Quinto-Cortés CDPapers in this archive, Rodrigues MFPapers in this archive, Saunack KPapers in this archive, Sellinger TPapers in this archive, Thornton KPapers in this archive, van Kemenade HPapers in this archive, Wohns AWPapers in this archive, Wong YPapers in this archive, Gravel SPapers in this archive, Kern ADPapers in this archive, Koskela JPapers in this archive, Ralph PLPapers in this archive, Kelleher JPapers in this archive
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, a large number of specialized 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 the tskit library. We summarize msprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized 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.
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