ArticleBMC bioinformatics2012
Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Asymmetric Cluster-Based Measures for Comparative Phylogenetics.Journal of computational biology : a journal of computational molecular cell biology · 2024Article
- Embedding gene trees into phylogenetic networks by conflict resolution algorithms.Algorithms for molecular biology : AMB · 2022Article
- Non-parametric correction of estimated gene trees using TRACTION.Algorithms for molecular biology : AMB · 2020Article
- The link between orthology relations and gene trees: a correction perspective.Algorithms for molecular biology : AMB · 2016Article
- Efficient Gene Tree Correction Guided by Genome Evolution.PloS one · 2016Article
- The inference of gene trees with species trees.Systematic biology · 2015Review
- Polytomy refinement for the correction of dubious duplications in gene trees.Bioinformatics (Oxford, England) · 2014Article
- DrML: probabilistic modeling of gene duplications.Journal of computational biology : a journal of computational molecular cell biology · 2014Article
- Gene tree correction guided by orthology.BMC bioinformatics · 2013Article
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3 authors.
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Abstract
backgroundGene tree - species tree reconciliation problems infer the patterns and processes of gene evolution within a species tree. Gene tree parsimony approaches seek the evolutionary scenario that implies the fewest gene duplications, duplications and losses, or deep coalescence (incomplete lineage sorting) events needed to reconcile a gene tree and a species tree. While a gene tree parsimony approach can be informative about genome evolution and phylogenetics, error in gene trees can profoundly bias the results.
resultsWe introduce efficient algorithms that rapidly search local Subtree Prune and Regraft (SPR) or Tree Bisection and Reconnection (TBR) neighborhoods of a given gene tree to identify a topology that implies the fewest duplications, duplication and losses, or deep coalescence events. These algorithms improve on the current solutions by a factor of n for searching SPR neighborhoods and n2 for searching TBR neighborhoods, where n is the number of taxa in the given gene tree. They provide a fast error correction protocol for ameliorating the effects of gene tree error by allowing small rearrangements in the topology to improve the reconciliation cost. We also demonstrate a simple protocol to use the gene rearrangement algorithm to improve gene tree parsimony phylogenetic analyses.
conclusionsThe new gene tree rearrangement algorithms provide a fast method to address gene tree error. They do not make assumptions about the underlying processes of genome evolution, and they are amenable to analyses of large-scale genomic data sets. These algorithms are also easily incorporated into gene tree parsimony phylogenetic analyses, potentially producing more credible estimates of reconciliation cost.
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