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Newer methods for tree building

Newer methods for tree building. Parsimony analysis Maximum likelihood Bayesian inference For all 3: Build an unrooted tree on one of these three criteria, ignore synapomorphy and symplesiomorphy , and pull root out on tree using outgroup. All computationally intense.

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Newer methods for tree building

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  1. Newer methods for tree building • Parsimony analysis • Maximum likelihood • Bayesian inference • For all 3: Build an unrooted tree on one of these three criteria, ignore synapomorphy and symplesiomorphy, and pull root out on tree using outgroup All computationally intense

  2. Newer methods for tree buildingSearch Criteria • Parsimony Analysis = build unrooted tree with the fewest character state changes • Maximum likelihood = given rules about how DNA sequences change over time, a tree can be found that reflects the most likely sequence of events • Bayesian inference = generates a posterior distribution for a parameter, composed of a phylogenetic tree and a model of evolution, based on the prior for that parameter and the likelihood of the data

  3. Pretty hard to do by hand…

  4. Rooted vs. unrooted trees A B C D f e A C e f g B D Basal node obvious vs. basal node unknown Rooted trees are way more fun! Just need to know which node is basal (oldest) Imagine pulling strings

  5. Rooted vs. unrooted trees Basal node obvious, basal node unknown

  6. Number of unrooted trees for 4 taxa = 3 A C A B B D C D A C D B

  7. Number of unrooted trees for 4 taxa = 3Number of rooted trees for 4 taxa = 15 A C A B B D Practice rooting C D A C D B

  8. Unrooted Tree of Herpes Viruses

  9. Number of trees increases with number of taxa • 4 taxa  3 unrooted trees • 8 taxa  10,395 unrooted trees • 10 taxa  2,027,025 unrooted trees • 22 taxa  3 x 1023 (almost a mole) • 50 taxa  3 x 1074 (More trees than the number of atoms in the universe) • “Exhaustive searches” of tree topologies are nearly impossible with modern data sets • Algorithms attempt to find best tree anyway Barry Hall, Phylogenetic Trees Made Easy

  10. Estimating confidence in trees: • Character conflict is common in data. We want to know if it is overwhelming the signal in the data. • We may not have collected enough data to estimate relationships confidently.

  11. Estimating confidence in trees: • Bootstrap support • If low, mentally collapse the node into a polytomy

  12. Breaking the Bifurcation Rule:Hard polytomies and Soft polytomies Cichlids

  13. Venereal syphilis http://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0002303

  14. Non-venereal Trepanomatoses 1950 50-100 million people

  15. Non-venereal Trepanomatoses 1950

  16. Endemic Trepanomatoses 1950 50-100 million 1970 1990 = 2.5 million

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