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 building Search 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 treesA B C D e f 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 = 3C A B B D C D A C D B

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

9. Unrooted
Tree of
Herpes
Viruses

10. 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

12. 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.

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

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

16. Venereal syphilis

17. Non-venereal Trepanomatoses
1950
million
people

18. Non-venereal Trepanomatoses
1950

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