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Jeremy G. Sumner,
Barbara R. Holland and
Peter D. Jarvis. The algebra of the general Markov model on phylogenetic trees and networks. In BMB, Vol. 74(4):858-880, 2012. Keywords: abstract network, phylogenetic network, phylogeny, split, split network, statistical model. Note: http://arxiv.org/abs/1012.5165.
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"It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the associated Hadamard transformation, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper, we rectify this shortcoming by showing how to extend the general Markov model on trees to include incompatible edges; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the "splitting" operator that generates the branching process on phylogenetic trees. For simplicity, we proceed by discussing the two state case and then show that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the Hadamard approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give an argument that our extension to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications. © 2011 Society for Mathematical Biology."
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Barbara R. Holland,
Steffi Benthin,
Peter J. Lockhart,
Vincent Moulton and
Katharina Huber. Using supernetworks to distinguish hybridization from lineage-sorting. In BMCEB, Vol. 8(202), 2008. Keywords: explicit network, from unrooted trees, hybridization, lineage sorting, phylogenetic network, phylogeny, reconstruction, supernetwork. Note: http://dx.doi.org/10.1186/1471-2148-8-202.
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"Background. A simple and widely used approach for detecting hybridization in phylogenies is to reconstruct gene trees from independent gene loci, and to look for gene tree incongruence. However, this approach may be confounded by factors such as poor taxon-sampling and/or incomplete lineage-sorting. Results. Using coalescent simulations, we investigated the potential of supernetwork methods to differentiate between gene tree incongruence arising from taxon sampling and incomplete lineage-sorting as opposed to hybridization. For few hybridization events, a large number of independent loci, and well-sampled taxa across these loci, we found that it was possible to distinguish incomplete lineage-sorting from hybridization using the filtered Z-closure and Q-imputation supernetwork methods. Moreover, we found that the choice of supernetwork method was less important than the choice of filtering, and that count-based filtering was the most effective filtering technique. Conclusion. Filtered supernetworks provide a tool for detecting and identifying hybridization events in phylogenies, a tool that should become increasingly useful in light of current genome sequencing initiatives and the ease with which large numbers of independent gene loci can be determined using new generation sequencing technologies. © 2008 Holland et al; licensee BioMed Central Ltd."
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Barbara R. Holland,
Glenn Conner,
Katharina Huber and
Vincent Moulton. Imputing Supertrees and Supernetworks from Quartets. In Systematic Biology, Vol. 56(1):57-67, 2007. Keywords: abstract network, from unrooted trees, phylogenetic network, phylogeny, Program Quartet, reconstruction, split network, supernetwork. Note: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.99.3215.
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"Inferring species phylogenies is an important part of understanding molecular evolution. Even so, it is well known that an accurate phylogenetic tree reconstruction for a single gene does not always necessarily correspond to the species phylogeny. One commonly accepted strategy to cope with this problem is to sequence many genes; the way in which to analyze the resulting collection of genes is somewhat more contentious. Supermatrix and supertree methods can be used, although these can suppress conflicts arising from true differences in the gene trees caused by processes such as lineage sorting, horizontal gene transfer, or gene duplication and loss. In 2004, Huson et al. (IEEE/ACM Trans. Comput. Biol. Bioinformatics 1:151-158) presented the Z-closure method that can circumvent this problem by generating a supernetwork as opposed to a supertree. Here we present an alternative way for generating supernetworks called Q-imputation. In particular, we describe a method that uses quartet information to add missing taxa into gene trees. The resulting trees are subsequently used to generate consensus networks, networks that generalize strict and majority-rule consensus trees. Through simulations and application to real data sets, we compare Q-imputation to the matrix representation with parsimony (MRP) supertree method and Z-closure, and demonstrate that it provides a useful complementary tool. Copyright © Society of Systematic Biologists."
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Barbara R. Holland,
Frédéric Delsuc and
Vincent Moulton. Visualizing Conflicting Evolutionary Hypotheses in Large Collections of Trees: Using Consensus Networks to Study the Origins of Placentals and Hexapods. In Systematic Biology, Vol. 54(1):66-76, 2005. Keywords: consensus. Note: http://hal-sde.archives-ouvertes.fr/halsde-00193050/fr/.
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"Many phylogenetic methods produce large collections of trees as opposed to a single tree, which allows the exploration of support for various evolutionary hypotheses. However, to be useful, the information contained in large collections of trees should be summarized; frequently this is achieved by constructing a consensus tree. Consensus trees display only those signals that are present in a large proportion of the trees. However, by their very nature consensus trees require that any conflicts between the trees are necessarily disregarded. We present a method that extends the notion of consensus trees to allow the visualization of conflicting hypotheses in a consensus network. We demonstrate the utility of this method in highlighting differences amongst maximum likelihood bootstrap values and Bayesian posterior probabilities in the placental mammal phylogeny, and also in comparing the phylogenetic signal contained in amino acid versus nucleotide characters for hexapod monophyly. Copyright © Society of Systematic Biologists."
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Martyn Kennedy,
Barbara R. Holland,
Russel D. Gray and
Hamish G. Spencer. Untangling Long Branches: Identifying Conflicting Phylogenetic Signals Using Spectral Analysis, Neighbor-Net, and Consensus Networks. In Systematic Biology, Vol. 54(4):620-633, 2005. Keywords: abstract network, consensus, NeighborNet, phylogenetic network, phylogeny. Note: http://awcmee.massey.ac.nz/people/bholland/pdf/Kennedy_etal_2005.pdf.
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