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Generalizing phylogenetics to infer shared evolutionary events

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Lightning talk presented at SSB Standalone Meetings in Baton Rouge, Louisiana, on 10 January 2017.

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Generalizing phylogenetics to infer shared evolutionary events

  1. 1. Generalizing phylogenetics to infer shared evolutionary events Jamie R. Oaks1 1Department of Biological Sciences, Auburn University January 10, 2017 Shared divergences Jamie Oaks – phyletica.org 1/12
  2. 2. Assumption: All processes of diversification affect each lineage independently and only cause bifurcating divergences. Shared divergences Jamie Oaks – phyletica.org 2/12
  3. 3. Shared divergences Jamie Oaks – phyletica.org 3/12
  4. 4. Shared divergences Jamie Oaks – phyletica.org 3/12
  5. 5. Shared divergences Jamie Oaks – phyletica.org 3/12
  6. 6. Why account for shared divergences? 1. Improve inference Shared divergences Jamie Oaks – phyletica.org 4/12
  7. 7. Why account for shared divergences? 1. Improve inference 2. Provide a framework for studying processes of co-diversification Shared divergences Jamie Oaks – phyletica.org 4/12
  8. 8. τ1 Shared divergences Jamie Oaks – phyletica.org 5/12
  9. 9. τ1 Shared divergences Jamie Oaks – phyletica.org 5/12
  10. 10. m1 m2 m3 m4 m5 τ1 τ2 τ1 τ1τ2 τ1τ2 τ3 τ1τ2 Shared divergences Jamie Oaks – phyletica.org 6/12
  11. 11. m1 m2 m3 m4 m5 τ1 τ2 τ1 τ1τ2 τ1τ2 τ3 τ1τ2 We want to infer the model and divergence times given variable characters (SNPs, AFLPs, indels) from across the genome Shared divergences Jamie Oaks – phyletica.org 6/12
  12. 12. Ecoevolity: Estimating evolutionary coevality CTMC model of characters evolving along genealogies Coalescent model of genealogies branching within populations Dirichlet-process or uniform prior across divergence models Gibbs sampling1 and reversible-jump MCMC2 to numerically sample models Analytically integrate over genealogies3 1 R. M. Neal (2000). Journal of Computational and Graphical Statistics 9: 249–265 2 P. J. Green (1995). Biometrika 82: 711–732 3 D. Bryant et al. (2012). Molecular Biology and Evolution 29: 1917–1932 Shared divergences Jamie Oaks – phyletica.org 7/12
  13. 13. Ecoevolity: Estimating evolutionary coevality CTMC model of characters evolving along genealogies Coalescent model of genealogies branching within populations Dirichlet-process or uniform prior across divergence models Gibbs sampling1 and reversible-jump MCMC2 to numerically sample models Analytically integrate over genealogies3 Fast, full-likelihood Bayesian method to infer patterns of co-diversification from genome-scale data 1 R. M. Neal (2000). Journal of Computational and Graphical Statistics 9: 249–265 2 P. J. Green (1995). Biometrika 82: 711–732 3 D. Bryant et al. (2012). Molecular Biology and Evolution 29: 1917–1932 Shared divergences Jamie Oaks – phyletica.org 7/12
  14. 14. qqq q q q q qq q qq q q qq q q q q q q q q q q q qqq q q qqq q q qq q q q qq q q qq q q qq q q qq q q qq qqq q q q qqq qqq qqq qqq qqq qqq q qq q q q q q q q qq q qq q q q q qq qqq qqq qq q qqq q q q q q qq q q qqq q q q q q q q q q qqq qqq qqq q q q qq q qqq q qq qqq q q q qqqqq q q q q q qq qq q q qq q q q qq q qq qqq q qq q qqq q q q qqq q qqq q q q qq q q q q q qq qq qq q qqq qqq qqq q qq qqq q q qqqq qq q q q q qq q qqq qq q q qqq qq q qq qqq q qq q q q qq q q qq qq qq qq qqqq qq q q qqqq q qq qq q q q q qq q q qq q q q q q q qq q qq q q qq q q q qqq q qq q q q qqqqqq q qqq q q q qq qqq q qqq q q qqq qqq qqq q qq qq q qq q qqq qqq qq qq q q qqq q q q q q q q q qq q q q q q qq q qqqq q q q qq qq q qqq q qq q q q q q q q qq q qq q q q qqq q q q q qq qq q qq q qqq q q q q qq qqq qqq q q q q qq qqq q qq q qq q qq qqq qq q q q q qq q q qq q q q qqq qqq q q q qqqq qqqqq qq q q qq q qq qq q qq qq q q q q q q q q qqqqqqq q q qq qqqq qqq q q q qqq q q q q q q q q q qqq q q q qqq qq q qq qq q q q q q qqq q q q q q qqqq q qqqq q qqqq qq q q q qqq qqqq q qq q q q qq q qqqqq q qq qq q q q q q q q qqq q q q qq qq q q q q qq qq q q q qq qqqq qq q qqq qq q qqq qq q q q q qq q qq q qqq qqq q q q q q q qq q qqqq q q qq q qqq q qq qq qq q q qqq qqq qqq qq q qqq qq q q q q qq q qqq qq qq qq qqq q q q q qq qqq qqq qqq q qq q qq q q q qqq qqq q q q qqq qq q q qq q q qq q q q qq qqqqqq q q q q qq qq q q q q q qq q qqqqq qqq qqq qq q q q qqqq qq q q q q qq qqqq q q q qqqq q qq q q qq q qq qqqq qq qq q qq q q qqq q qq qqq q q q qqq qqq q q q q qq q q q qqq q qq qq q qq q q q qq qq q qq q qq qqq q q q qq q q q q qqq qq q q qq qqq qqq q q q qqq qq q q q q q q q q qq q qq qqq q qqqqq qq q q q qq q q qqq q q q qqqqq q q q q qq q q q q q q q q q q qqq qq q q q q qqq qq qqqq qq qq q qq qq q q qq qq qqq q q q qqq qq q qq qq q q qqq q qq qq q q q qq qq qq q qqq qqqq q q qqqq q q qqq q qq qq q q qq qqq qq qq q q q qq qqq qqq qq qqqq q qqqq q qqq q qq q q qq q qq q qq q qqqq q q q qqq q q q q q q qqq qq q qq q q q q qqq q q q q q q qqq qq qq qq qq qqq q qqq qq q qqqq q q q qq q q q q q q q q q q q q q q q q qq q qq qqq qq q q qqqqq qq q q qq qq q q q q qqqqqq qqq q q q q qq q q q qqqq qqq qq qqqq qq qq qqq q qq q qq q qqq qqq q qq q q q q qqq q q q q q q q q qqq q q q qqq q q q q qq qqq q q q q qq q q q qqq q q qq q q q qqqq q q q q qqq q q q qqqq q q qqq q q q qq q q q q q qqqqqqqq q qq q q q qqq qqq qq q q qqq qq qqq qq q q qq qq q q qq q qq q qq qqq q qq q qq q q q q qq qqq q q q q qq qqq qqq q q q q q q q q qq q qqqq q q q qq q q q q q q q q qq q qq q qq q q q qq q q q qq qq qqq q qq q qq qq qq q q q q q qq q q qq qq q qqq qqqqqq q qqq qq qqq qq qq q q qq q qqq qq q q q q qq q q q q qq q q q q q q q q q q qq q q q q q q qq q q qq q q qq qq q q q q q q q qq q qqq qq qqqq q q q qqqq q q q qq qqq q q q qqq q q q q q q qq q qqq qqq qqq qqq q qqq qq qq q qq q q q qqqq qq q q q q q q q q q q q qq qqq q qq qqq q qq qqqqq q q q q qq q qqq q q q qqq q q q q q q qq q qqq qq qqqq q q qqqq qqq qqq q q q qqqq q q q q q q q q qq q q q q qqq q q q q qq qqq q qq qq q q q q qq q q qq q q qq q q qq q q q q qq q q q q qqq qqq qq q q q q q q q q qq qq q q qq qq q qqqq q q qqq qqq qqq qq q q q q q q qq q q q qq q qq qqq q q q qqq q qq q qq q q q q qq qqq q q q q q q q q q qqq q q q qq q q q q qq q q qq q qqq q q qqq qqq q qq qqq qq q q q qq qq q qq qqq q q qq q q qqq qqq qq q qq q q qq q q q qqq q q q qqq qqqqqq q qq q q q qq qqq q q q q q qq q q q q qq q qq q q q q q q qqq q qq qq q qqqq q q qqq q qq q q q qq qqq q qqq qqq q q q q qq qq q qqqq q qqq q qq q q q q q qq q qq q q q q qq qq q q q q q qq q q q qq q q qq qq q q q q qqq qqq q q q q qqq qq qq q q qq qqq qq q q q q qq q q qq qqq q q q qqq q q q qq q q q q qqq q q q q qq qq q qq q qq q qqq q q q q qqqq q q qqq qq q qq qqq q q q qq q qqq qq q q qq q q qq q q qqq q q q q q qqq q q qq q q q qqq q qq q q q q qq qq q q qq qq q qqqq qq qqq q qq q qq qq q qqq qqq qq q qqq q q q q qq q q q qqq qqq qqqqqqq qq qqqqqq q q q q q q qqq qq q q qq q q qqqq qqq qqqqq qq qq q qq qqq qqq q qq qqqqq q q q q q q q qqq q qq q q q q qq q qq q q qq qq q qqqqq qq q q qq q q q qqq qq q q q q qqq q q qqqq q q qqqqq q q qqq q q q qq q qqq q qq qqq qqq q qqq qq qqq qqq q qq qq q qqqq q qq q q q q q q q q q qq qqq qqq qqq qq qqqq q q q q qqq q q qq qqqq qqqq q q q q q qq q qqq q qqq qq qqqq qq q q q qqq qqq q q q qqqq q q qqq qqq qqq qq q qqqqqqqqq qqq q qq qqq q q q q qqqqq qqq qqq q qq q qq q qq qq q q qq qqq q qq q q qq qq qqqqq q qq q q qq q q q qq q qqq q qq q qq q qq q q q qqq q q q q q q qq q qq q q q q qq q q qqq q q q q q qqqq qq qqqqqq qqq q q q q q qqq q qq qqq q qqq q q q q q q qqq q q q q qq q q qqq q qqq qqq q q q q q q qq q qqqqq q q q q qqqqqq qqqq qq q q q qqq q qqqq q qq q q q q q qqqq q qqq q q q 0.00 0.02 0.04 0.06 0.08 0.000.020.040.06 True divergence time Estimateddivergencetime The true model is in the 95% credible set 97% of the time Shared divergences Jamie Oaks – phyletica.org 8/12
  15. 15. Everything is on GitHub. . . Software: Ecoevolity: https://github.com/phyletica/ecoevolity Open-Science Notebook: https://github.com/phyletica/ecoevolity-experiments Shared divergences Jamie Oaks – phyletica.org 9/12
  16. 16. Next step: A general framework Generalize Bayesian phylogenetics to incorporate shared divergences Sample models numerically via reversible-jump MCMC Benefits: Improve phylogenetic inference Framework for studying processes of co-diversification τ1τ2τ3 Shared divergences Jamie Oaks – phyletica.org 10/12
  17. 17. Acknowledgments Ideas and feedback: Leach´e Lab Minin Lab Mark Holder Tracy Heath Michael Landis Computation: Funding: Photo credits: PhyloPic! Shared divergences Jamie Oaks – phyletica.org 11/12
  18. 18. Questions? joaks@auburn.edu c 2007 Boris Kulikov boris-kulikov.blogspot.com Shared divergences Jamie Oaks – phyletica.org 12/12
  19. 19. Solution: Accommodate shared divergence models Advantage: More data to estimate shared parameters True history τ1τ2τ3 Problem: Current methods only consider general model Consequence: Unnecessary parameters introduce error Current tree model τ1 τ2 τ3τ4 τ5 τ6 τ7 τ8 Shared divergences Jamie Oaks – phyletica.org 12/12

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