ArticleBMC genomics2020
Forcing external constraints on tree inference using ASTRAL.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comparison of phylogenetic trees defined on different but mutually overlapping sets of taxa: A review.Ecology and evolution · 2024Review
- Artifactual Orthologs and the Need for Diligent Data Exploration in Complex Phylogenomic Datasets: A Museomic Case Study from the Andean Flora.Systematic biology · 2024Article
- Generation of accurate, expandable phylogenomic trees with uDance.Nature biotechnology · 2024Article
- Quartets enable statistically consistent estimation of cell lineage trees under an unbiased error and missingness model.Algorithms for molecular biology : AMB · 2023Article
- Invasive Californian death caps develop mushrooms unisexually and bisexually.Nature communications · 2023Article
- Weighted ASTRID: fast and accurate species trees from weighted internode distances.Algorithms for molecular biology : AMB · 2023Article
- Recent progress on methods for estimating and updating large phylogenies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Review
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2 authors.
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Abstract
backgroundTo account for genome-wide discordance among gene trees, several widely-used methods seek to find a species tree with the minimum distance to input gene trees. To efficiently explore the large space of species trees, some of these methods, including ASTRAL, use dynamic programming (DP). The DP paradigm can restrict the search space, and thus, ASTRAL and similar methods use heuristic methods to define a restricted search space. However, arbitrary constraints provided by the user on the output tree cannot be trivially incorporated into such restrictions. The ability to infer trees that honor user-defined constraints is needed for many phylogenetic analyses, but no solution currently exists for constraining the output of ASTRAL.
resultsWe introduce methods that enable the ASTRAL dynamic programming to infer constrained trees in an effective and scalable manner. To do so, we adopt a recently developed tree completion algorithm and extend it to allow multifurcating input and output trees. In simulation studies, we show that the approach for honoring constraints is both effective and fast. On real data, we show that constrained searches can help interrogate branches not recovered in the optimal ASTRAL tree to reveal support for alternative hypotheses.
conclusionsThe new algorithm is added ASTRAL to all user-provided constraints on the species tree.
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