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Huber, Katharina T, Moulton, Vincent 
ORCID: https://orcid.org/0000-0001-9371-6435, Sagot, Marie-France and Sinaimeri, Blerina
(2019)
Exploring and visualising spaces of tree reconciliations.
Systematic Biology, 68 (4).
pp. 607-618.
ISSN 1063-5157
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Abstract
Tree reconciliation is the mathematical tool that is used to investigate the coevolution of organisms, such as hosts and parasites. A common approach to tree reconciliation involves specifying a model that assigns costs to certain events, such as cospeciation, and then tries to find a mapping between two specified phylogenetic trees which minimises the total cost of the implied events. For such models, it has been shown that there may be a huge number of optimal solutions, or at least solutions that are close to optimal. It is therefore of interest to be able to systematically compare and visualise whole collections of reconciliations between a specified pair of trees. In this paper, we consider various metrics on the set of all possible reconciliations between a pair of trees, some that have been defined before but also new metrics that we shall propose. We show that the diameter for the resulting spaces of reconciliations can in some cases be determined theoretically, information that we use to normalise and compare properties of the metrics. We also implement the metrics and compare their behaviour on several host parasite datasets, including the shapes of their distributions. In addition, we show that in combination with multidimensional scaling, the metrics can be useful for visualising large collections of reconciliations, much in the same way as phylogenetic tree metrics can be used to explore collections of phylogenetic trees. Implementations of the metrics can be downloaded from: https://team.inria.fr/erable/en/team-members/blerina-sinaimeri/reconciliation-distances/
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | reconciliation,reconciliation space,coevolution,phylogenetic tree |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 17 Oct 2018 15:31 |
| Last Modified: | 20 Apr 2023 04:30 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/68591 |
| DOI: | 10.1093/sysbio/syy075 |
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