Yishu Wang1,2, Arnaud Mary1,2, Marie-France Sagot1,2, Blerina Sinaimeri1,2. 1. Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, F-69622 Villeurbanne, France. 2. Inria Grenoble, Montbonnot 38334, France.
Abstract
MOTIVATION: Phylogenetic tree reconciliation is the method of choice in analyzing host-symbiont systems. Despite the many reconciliation tools that have been proposed in the literature, two main issues remain unresolved: (i) listing suboptimal solutions (i.e. whose score is 'close' to the optimal ones) and (ii) listing only solutions that are biologically different 'enough'. The first issue arises because the optimal solutions are not always the ones biologically most significant; providing many suboptimal solutions as alternatives for the optimal ones is thus very useful. The second one is related to the difficulty to analyze an often huge number of optimal solutions. In this article, we propose Capybara that addresses both of these problems in an efficient way. Furthermore, it includes a tool for visualizing the solutions that significantly helps the user in the process of analyzing the results. AVAILABILITY AND IMPLEMENTATION: The source code, documentation and binaries for all platforms are freely available at https://capybara-doc.readthedocs.io/. CONTACT: yishu.wang@univ-lyon1.fr or blerina.sinaimeri@inria.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Phylogenetic tree reconciliation is the method of choice in analyzing host-symbiont systems. Despite the many reconciliation tools that have been proposed in the literature, two main issues remain unresolved: (i) listing suboptimal solutions (i.e. whose score is 'close' to the optimal ones) and (ii) listing only solutions that are biologically different 'enough'. The first issue arises because the optimal solutions are not always the ones biologically most significant; providing many suboptimal solutions as alternatives for the optimal ones is thus very useful. The second one is related to the difficulty to analyze an often huge number of optimal solutions. In this article, we propose Capybara that addresses both of these problems in an efficient way. Furthermore, it includes a tool for visualizing the solutions that significantly helps the user in the process of analyzing the results. AVAILABILITY AND IMPLEMENTATION: The source code, documentation and binaries for all platforms are freely available at https://capybara-doc.readthedocs.io/. CONTACT: yishu.wang@univ-lyon1.fr or blerina.sinaimeri@inria.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.