ARGscape: A modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909831544176640 |
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| author | Talbot, Christopher Bradburd, Gideon |
| author_facet | Talbot, Christopher Bradburd, Gideon |
| contents | Ancestral recombination graphs (ARGs) encode the complete genealogical history of a population of recombining lineages. ARGs, and their succinct representation, tree sequences, are increasingly central to modern population genetics methods, yet building an intuition for ARGs remains challenging. This is particularly true when analyzing ancestry in a geographic context, as there is a critical lack of dedicated, interactive tools capable of visualizing ARGs as spatiotemporal objects. To address this gap, we introduce ARGscape, an interactive platform for simulating, analyzing, and visualizing ARGs across space and time. ARGscape provides a user-friendly graphical interface featuring dynamic 2- and 3-dimensional visualizations to explore ARGs through space and time, as well as a novel "spatial diff" visualization for quantitative comparison of geographic inference methods. ARGscape is an innovative, unified framework that seamlessly integrates leading command-line, Python, and R-based tools for ARG simulation, manipulation, and use in spatiotemporal inference into both graphical and command-line interfaces. By integrating these various functionalities, ARGscape facilitates novel data exploration and hypothesis generation, while lowering the barrier to entry for spatiotemporal ARG analysis in both research and education use-cases. ARGscape is built with a Python FastAPI backend and a React/TypeScript frontend. It is freely available as a live demo at https://www.argscape.com and as a Python package on PyPI (pip install argscape). The source code and documentation are available on GitHub at https://github.com/chris-a-talbot/argscape. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07255 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ARGscape: A modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs Talbot, Christopher Bradburd, Gideon Populations and Evolution Ancestral recombination graphs (ARGs) encode the complete genealogical history of a population of recombining lineages. ARGs, and their succinct representation, tree sequences, are increasingly central to modern population genetics methods, yet building an intuition for ARGs remains challenging. This is particularly true when analyzing ancestry in a geographic context, as there is a critical lack of dedicated, interactive tools capable of visualizing ARGs as spatiotemporal objects. To address this gap, we introduce ARGscape, an interactive platform for simulating, analyzing, and visualizing ARGs across space and time. ARGscape provides a user-friendly graphical interface featuring dynamic 2- and 3-dimensional visualizations to explore ARGs through space and time, as well as a novel "spatial diff" visualization for quantitative comparison of geographic inference methods. ARGscape is an innovative, unified framework that seamlessly integrates leading command-line, Python, and R-based tools for ARG simulation, manipulation, and use in spatiotemporal inference into both graphical and command-line interfaces. By integrating these various functionalities, ARGscape facilitates novel data exploration and hypothesis generation, while lowering the barrier to entry for spatiotemporal ARG analysis in both research and education use-cases. ARGscape is built with a Python FastAPI backend and a React/TypeScript frontend. It is freely available as a live demo at https://www.argscape.com and as a Python package on PyPI (pip install argscape). The source code and documentation are available on GitHub at https://github.com/chris-a-talbot/argscape. |
| title | ARGscape: A modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs |
| topic | Populations and Evolution |
| url | https://arxiv.org/abs/2510.07255 |