Population-scale Ancestral Recombination Graphs with tskit 1.0

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Authors: Ben Jeffery, Yan Wong, Kevin Thornton, Georgia Tsambos, Gertjan Bisschop, Yun Deng, E. Castedo Ellerman, Thomas B. Forest, Halley Fritze, Daniel R. Goldstein, Gregor Gorjanc, Graham Gower
+40 more Simon Gravel, Jeremy Guez, Benjamin C. Haller, Andrew D. Kern, Lloyd Kirk, Ivan Krukov, Hanbin Lee, Brieuc Lehmann, Hossameldin Loay, Matthew M. Osmond, Duncan S. Palmer, Pope Nathaniel, Aaron P. Ragsdale, Duncan Robertson, Murillo F. Rodrigues, Hugo van Kemenade, Clemens Weiß, Anthony Wilder Wohns, Brian C. Zhang, Brian C. Zhang, Marianne Aspbury, Nikolas A. Baya, Saurabh Belsare, Arjun Biddanda, Francisco Campuzano Jiménez, Ariella Gladstein, Bing Guo, Savita Karthikeyan, Warren W. Kretzschmar, Inés Rebollo, Kumar Saunack, Ruhollah Shemirani, Alexis Simon, Chris Smith, Jeet Sukumaran, Jonathan Terhorst, Per Unneberg, Ao Zhang, Peter Ralph, Jerome Kelleher
Cited by: 1

Abstract

Ancestral recombination graphs (ARGs) are an increasingly important component of population and statistical genetics. The tskit library has become key infrastructure for the field, providing an expressive and general representation of ARGs together with a suite of efficient fundamental operations. In this note, we announce tskit version 1.0, describe its underlying rationale, and document its stability guarantees. These guarantees provide a foundation for durable computational artefacts and support long-term reproducibility of code and analyses.

Fields of Study & Subjects

Genetic Associations and Epidemiology Genome Rearrangement Algorithms Genetic Neurodegenerative Diseases

Publication details

Journal / source
arXiv (Cornell University)
Publication date
10 February 2026
Document type
Preprint