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ARGscape: a modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs
Christopher A Talbot1,2, Gideon S Bradburd1
1Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, United States.
Bioinformatics (Oxford, England)
|June 25, 2026
Summary
ARGscape unifies tools for ancestral recombination graph (ARG) analysis, enhancing spatiotemporal demographic inference. This framework integrates simulation, manipulation, and visualization for population genetics research.
Area of Science:
- Population genetics
- Computational biology
- Bioinformatics
Background:
- Ancestral recombination graphs (ARGs) are crucial for modern population genetics.
- Current ARG-based methods for spatiotemporal demographic inference are underutilized due to fragmented workflows and limited exploratory tools.
Purpose of the Study:
- To introduce ARGscape, a unified framework designed to streamline and enhance the use of ARGs in population genetics.
- To provide integrated tools for ARG simulation, manipulation, and spatiotemporal inference.
Main Methods:
- ARGscape offers both graphical and command-line interfaces.
- Features dynamic 2D and 3D visualizations, including a novel "spatial diff" visualization for comparing geographic inference methods.
- Integrates established and novel ARG analysis tools.
Main Results:
- ARGscape facilitates novel data exploration and hypothesis generation.
- It bridges the gap between ARG methods development and empirical application.
- The framework supports educational uses by simplifying complex ARG analyses.
Conclusions:
- ARGscape addresses the underutilization of ARG-based methods in empirical population genetics.
- The integrated framework and advanced visualizations empower researchers to perform more sophisticated spatiotemporal demographic inference.
- ARGscape promotes wider adoption and application of ARG methodologies in the field.
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