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SuperQ: Computing Supernetworks from Quartets
Jan.-Feb. 2013 (vol. 10 no. 1)
pp. 151-160
Stefan Grunewald, CAS-MPG Partner Inst. for Comput. Biol., Shanghai, China
Andreas Spillner, Dept. of Math. & Comput. Sci., Univ. of Greifswald, Greifswald, Germany
Sarah Bastkowski, Sch. of Comput. Sci., Univ. of East Anglia, Norwich, UK
Anja Bogershausen, Dept. of Math. & Comput. Sci., Univ. of Greifswald, Greifswald, Germany
Vincent Moulton, Sch. of Comput. Sci., Univ. of East Anglia, Norwich, UK
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.
Index Terms:
Phylogeny,Vegetation,Computational biology,Bioinformatics,Visualization,Data visualization,Electronic mail,split network,Supertree,phylogenetic network,consensus network,supernetwork
Citation:
Stefan Grunewald, Andreas Spillner, Sarah Bastkowski, Anja Bogershausen, Vincent Moulton, "SuperQ: Computing Supernetworks from Quartets," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 1, pp. 151-160, Jan.-Feb. 2013, doi:10.1109/TCBB.2013.8
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