ArticleJournal of computational biology : a journal of computational molecular cell biology2013
Reconciliation revisited: handling multiple optima when reconciling with duplication, transfer, and loss.
Article in Journal of computational biology : a journal of computational molecular cell biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Investigating Additive and Replacing Horizontal Gene Transfers Using Phylogenies and Whole Genomes.Genome biology and evolution · 2024Article
- virDTL: Viral Recombination Analysis Through Phylogenetic Reconciliation and Its Application to Sarbecoviruses and SARS-CoV-2.Journal of computational biology : a journal of computational molecular cell biology · 2023Article
- A complete theoretical framework for inferring horizontal gene transfers using partial order sets.PloS one · 2023Article
- Phylogenetic reconciliation.PLoS computational biology · 2022Article
- Tree Reconciliation Methods for Host-Symbiont Cophylogenetic Analyses.Life (Basel, Switzerland) · 2022Article
- Efficiently sparse listing of classes of optimal cophylogeny reconciliations.Algorithms for molecular biology : AMB · 2022Article
- Deciphering Microbial Gene Family Evolution Using Duplication-Transfer-Loss Reconciliation and RANGER-DTL.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Maximum parsimony reconciliation in the DTLOR model.BMC bioinformatics · 2021Article
- Systematic Detection of Large-Scale Multigene Horizontal Transfer in Prokaryotes.Molecular biology and evolution · 2021Article
- ASTRAL-Pro: Quartet-Based Species-Tree Inference despite Paralogy.Molecular biology and evolution · 2020Article
- Counting and sampling gene family evolutionary histories in the duplication-loss and duplication-loss-transfer models.Journal of mathematical biology · 2020Article
- Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model.BMC bioinformatics · 2019Article
- Hierarchical clustering of maximum parsimony reconciliations.BMC bioinformatics · 2019Article
- Gene tree species tree reconciliation with gene conversion.Journal of mathematical biology · 2019Article
- Horizontal gene transfer in human-associated microorganisms inferred by phylogenetic reconstruction and reconciliation.Scientific reports · 2019Article
- RANGER-DTL 2.0: rigorous reconstruction of gene-family evolution by duplication, transfer and loss.Bioinformatics (Oxford, England) · 2018Article
- On the impact of uncertain gene tree rooting on duplication-transfer-loss reconciliation.BMC bioinformatics · 2018Article
- DTL reconciliation repair.BMC bioinformatics · 2017Article
- Biologically feasible gene trees, reconciliation maps and informative triples.Algorithms for molecular biology : AMB · 2017Article
- Phylogenetic framework for coevolutionary studies: a compass for exploring jungles of tangled trees.Current zoology · 2016Article
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3 authors.
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Abstract
Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While duplication-loss (DL) reconciliation leads to a unique maximum-parsimony solution, duplication-transfer-loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult to infer the true evolutionary history of the gene family. This problem is further exacerbated by the fact that different event cost assignments yield different sets of optimal reconciliations. Here, we present an effective, efficient, and scalable method for dealing with these fundamental problems in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We show that even gene trees with only a few dozen genes often have millions of optimal reconciliations and present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn(2)) time per sample, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mappings and event assignments and to investigate the impact of varying event costs. We apply our method to a biological dataset of approximately 4700 gene trees from 100 taxa and observe that 93% of event assignments and 73% of mappings remain consistent across different multiple optima. Our analysis represents the first systematic investigation of the space of optimal DTL reconciliations and has many important implications for the study of gene family evolution.
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