SuperQ:computing supernetworks from quartets

Grünewald, Stefan, Spillner, Andreas, Bastkowski, Sarah, Bögershausen, Anja and Moulton, Vincent (2013) SuperQ:computing supernetworks from quartets. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10 (1). pp. 151-60. ISSN 1557-9964

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Abstract

Supertrees are a commonly used tool in phylogenetics to summarize collections of partial phylogenetic trees. As a generalization of supertrees, phylogenetic supernetworks allow, in addition, the visual representation of conflict between the trees that is not possible to observe with a single tree. Here, we introduce SuperQ, a new method for constructing such supernetworks (SuperQ is freely available at >www.uea.ac.uk/computing/superq.). It works by first breaking the input trees into quartet trees, and then stitching these together to form a special kind of phylogenetic network, called a split network. This stitching process is performed using an adaptation of the QNet method for split network reconstruction employing a novel approach to use the branch lengths from the input trees to estimate the branch lengths in the resulting network. Compared with previous supernetwork methods, SuperQ has the advantage of producing a planar network. We compare the performance of SuperQ to the Z-closure and Q-imputation supernetwork methods, and also present an analysis of some published data sets as an illustration of its applicability.

Item Type: Article
Uncontrolled Keywords: computational biology,databases, genetic,genes, fungal,genes, plant,models, genetic,phylogeny,software
Faculty \ School: Faculty of Science > School of Computing Sciences
University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Computational biology of RNA
University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Phylogenetics
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Depositing User: Pure Connector
Date Deposited: 03 Feb 2014 11:18
Last Modified: 25 Jul 2018 09:28
URI: https://ueaeprints.uea.ac.uk/id/eprint/47444
DOI: 10.1109/TCBB.2013.8

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