a network framework to explore phylogenetic structure in genomic data
TRANSCRIPT
A network framework to explore phylogeneticstructure in genomic data
Guifang Zhou 1, Jeremy Ash 2, Wen Huang 3, Melissa Marchand 4, David Morris 1,Paul Van Dooren 3, James C. Wilgenbusch 5, Jeremy M. Brown 1, Kyle A. Gallivan 4
1Department of Biological Sciences, Louisiana State University2Bioinformatics Research Center, North Carolina State University
3ICTEAM Institute, Université catholique de Louvain4Department of Mathematics, Florida State University
5Minnesota Supercomputing Institute, University of Minnesota
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Motivations
Phylogenetic analyses often produce large sets ofcompeting trees
Summarize interesting evolutionary history:HybridizationRecombinationHorizontal Gene TransferIncomplete Lineage Sorting
Identify Systematic Error
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Shortcomings of Current Approaches
Consensus treeDiscards information concerning competing trees
Dimensionality ReductionMay be difficult to interpret
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Shortcomings of Current Approaches
ClusteringBased on pairwise tree to tree distanceOnly consider nonnegative links
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Our Approaches
Tree topologies Bipartitions within treetopologies
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Our Approaches
Apply graph-based methods to understand relationship among:
Tree topologies Bipartitions within treetopologies
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Application
Yeast dataset with 5 species, 106 loci106 gene trees were reconstructed using maximumparsimony
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Topology-based Network Analysis
Affinity matrixReciprocal of pairwisedistances
Detect communitiesDiscovered 11 communities
Consensus trees for eachcommunity
Top 2 recovers the top 2candidate species trees 62/106
17/10611/106
4/106
3/106
2/106
2/106
2/106
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Bipartition-based Network Analysis
Covariance matrix based on presence or absence ofbipartitions in the gene trees
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TreeScaper Software
Available on GitHub
https://github.com/whuang08/TreeScaper
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Acknowledgements
Computing support from FSU’s Research ComputingCenter and HPC@LSUThe National Science Foundation for funding to supportsome of this work (ABI-1262476)
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