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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 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
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Pretty hard to do by hand…
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Rooted vs. unrooted trees
Basal node obvious vs. basal node unknownRooted trees are way more fun!
Just need to know which node is basal (oldest) Imagine pulling strings
A B C D
e f
g
A
B
C
D
e f
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Rooted vs. unrooted trees
Basal node obvious, basal node unknown
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Number of unrooted trees for 4 taxa = 3A
B
C
D
A
C
B
D
A
D
C
B
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Number of unrooted trees for 4 taxa = 3Number of rooted trees for 4 taxa = 15
A
B
C
D
A
C
B
D
A
D
C
B
Practice rooting
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UnrootedTree of HerpesViruses
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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
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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.
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Estimating confidence in trees:
• Bootstrap support• If low, mentally collapse the node into a
polytomy
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Breaking the Bifurcation Rule:Hard polytomies and Soft polytomies
Cichlids
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Venereal syphilis
http://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0002303
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195050-100 millionpeople
Non-venereal Trepanomatoses
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1950
Non-venereal Trepanomatoses
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195050-100million
1970
Endemic Trepanomatoses
1990 = 2.5 million