ReviewFrontiers in bioinformatics2026
Human ancestries simulation and inference: a review of ancestral recombination graph-based approaches.
Review in Frontiers in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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2 authors.
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Abstract
The importance of the ancestral recombination graph (ARG) in population genetics is undeniable. An important theoretical tool, the main obstacle to its widespread usage is the computational cost required to match the ever-increasing scale of the data being analyzed. Many of these difficulties have been overcome in the past 2 decades, which have consequently seen the development of increasingly sophisticated ARG simulation and inference software. Nonetheless, challenges remain, especially in the area of ancestry inference. This study is a comprehensive review of ARG simulation and inference programs that have emerged in the past 3 decades to meet the need for scalable and flexible ancestry simulation and inference solutions. It specifically focuses on their performance, usability, and the biological realism of the underlying algorithm and primarily aims to provide a technical overview of the field for researchers seeking to design and implement their own coalescent-with-recombination algorithm. As a complement to this article, we have compiled the links to software, source code, and documentation and made them available at https://patrickfournier.ca/publications/arg-software-review/graph.
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