ArticleBioinformatics (Oxford, England)2026
ARGscape: a modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs.
Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Interactive exploration of biobank-scale ancestral recombination graphs with Lorax.Bioinformatics (Oxford, England) · 2026Article
- Interactive exploration of biobank-scale ancestral recombination graphs with Lorax.bioRxiv : the preprint server for biology · 2026Article
- Tracing the evolutionary histories of ultra-rare variants using variational dating of large ancestral recombination graphs.bioRxiv : the preprint server for biology · 2026Article
- A Pandemic-Scale Ancestral Recombination Graph for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025Article
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2 authors.
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Abstract
summaryAncestral recombination graphs (ARGs) are increasingly central to modern population genetics, yet ARG-based methods for spatiotemporal demographic inference remain underutilized in empirical settings due to fragmented workflows and a lack of exploratory tools. ARGscape addresses this by providing a unified framework, seamlessly integrating established and novel tools for ARG simulation, manipulation, and spatiotemporal inference into both graphical and command-line interfaces. ARGscape features dynamic 2- and 3-dimensional visualizations and a novel "spatial diff" visualization for quantitative comparison of ARG-based geographic inference methods. By integrating these various functionalities, ARGscape facilitates novel data exploration and hypothesis generation, bridging the gap between methods development and empirical adoption, and enabling educational uses. AVAILABILITY AND IMPLEMENTATION: ARGscape is available as a Python package on PyPI and as a live website for educational and simple demonstrative purposes at https://www.argscape.com. The source code and documentation are available on GitHub at https://github.com/chris-a-talbot/argscape.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.