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TreeScaper: Software to Visualize and Extract Phylogenetic Signals from Sets of Trees
- 1. TreeScaper: Software to visualize and extract phylogenetic signals from sets of trees Guifang Zhou 1, Wen Huang 3, Melissa Marchand 4, Jeremy Ash 2, David Morris 1, Pual Van Dooren 3, Jim C. Wilgenbusch 5, Jeremy M. Brown 1, Kyle A. Gallivan 4 1Department of Biological Sciences, Louisiana State University 2Bioinformatics Research Center, North Carolina State University 3ICTEAM Institute, Université catholique de Louvain 4Department of Mathematics, Florida State University 5Minnesota Supercomputing Institute, University of Minnesota June 21, 2016 June 21, 2016
- 2. Motivations Phylogenetic analyses often produce large sets of competing trees Summarize interesting evolutionary history: Hybridization Recombination Horizontal Gene Transfer Incomplete Lineage Sorting Identify Systematic Error June 21, 2016
- 3. Shortcomings of Current Approaches Consensus tree Discards information concerning competing trees Dimensionality Reduction May be difficult to interpret June 21, 2016
- 4. Shortcomings of Current Approaches Clustering Based on pairwise tree to tree distance Only consider nonnegative links June 21, 2016
- 5. Our Approaches Apply graph-based methods to understand relationship among: Tree topologies Bipartitions within tree topologies June 21, 2016
- 6. TreeScaper (Version 1) NLDR Optimization Algorithm Linear iteration Majorization Gauss-Newton Stochastic gradient descent MCMC simulated annealing Cost functions Kruskal-1 stress Normalized stress Sammon stress Curvilinear components analysis Dimension Estimator Nearest neighbor estimator Correlation dimension Maximum likelihood estimator Visualization June 21, 2016
- 7. TreeScaper (Version 2) NLDR Dimensionality estimation New input data types Distance/Affinity matrix Robinson-Foulds (Unweighted/Weighted) Matching Subtree Prune and Regraft Covariance matrix Community Detection methods Configuration Null Model Constant Potts Model Erdos-Renyi Null Model No Null Model Interactive visualization interface June 21, 2016
- 8. Application Yeast dataset with 5 species, 106 loci 106 gene trees were reconstructed using maximum parsimony June 21, 2016
- 9. Topology-based Network Analysis Affinity matrix Reciprocal of pairwise distances Detect communities Discovered 11 communities Consensus trees for each community Top 2 recovers the top 2 candidate species trees 62/106 17/106 11/106 4/106 3/106 2/106 2/106 2/106 · · · June 21, 2016
- 10. Bipartition-based Network Analysis Covariance matrix based on presence or absence of bipartitions in the gene trees June 21, 2016
- 11. TreeScaper Software Available on GitHub https://github.com/whuang08/TreeScaper June 21, 2016
- 12. TreeScaper Software Available on GitHub https://github.com/whuang08/TreeScaper June 21, 2016
- 13. Acknowledgements Computing support from FSU’s Research Computing Center and HPC@LSU The National Science Foundation for funding to support some of this work (ABI-1262476) June 21, 2016