Processing

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Processing Testing Phylogenetic Trees
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Rooting
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Rooting 1. Outgroup Rooting Based on External
Information. 2. Midpoint Rooting Direct a
posteriori use of the ultrametricity
assumption. 3. Largest-Genetic-Variability-Group
Rooting Indirect a posteriori use of the
ultrametricity assumption.
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Rooting with outgroup
plant
plant
Unrooted tree
plant
Rooted tree
bacterial outgroup
plant
Monophyletic group
plant
plant
animal
Monophyletic group
animal
root
animal
animal
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Midpoint rooting
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Largest variation Most ancient
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Species Divergence Times
If we know T1 and the rate of evolution, then we
can infer T2.
If we know T2 and the rate of evolution, then we
can infer T1.
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If T1 is known
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If T2 is known
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Topological comparisons
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Penny and Hendy's topological distance (dT) A
commonly used measure of dissimilarity between
two tree topologies. The measure is based on tree
partitioning. dT 2c c the number of
partitions resulting in different divisions of
the OTUs in the two tree topologies under
consideration.
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Trees inferred from the analysis of a particular
data set are called fundamental trees, i.e., they
summarize the phylogenetic information in a data
set. Consensus trees are trees that summarize
the phylogenetic information in a set of
fundamental trees.
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In a strict consensus tree, all conflicting
branching patterns are collapsed into
multifurcations. In a X majority-rule
consensus trees, a branching pattern that occurs
with a frequency of X or more is adopted. When
X 100, the majority-rule consensus tree will
be identical with the strict consensus tree.
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A tree is an evolutionary hypothesis
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How do we know that the inferred tree is correct?
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Caminalcules are a group of artificial organisms
(belonging to the genus Caminalculus) that were
invented by Dr. Joseph H. Camin from the
University of Kansas. Interested in how
taxonomists group species, he designed these
creatures to show an evolutionary pattern of
divergence and diversification in morphology.
There are 29 recent species of Caminalculus and
48 fossil forms. The Caminalcules first appeared
in print in the journal Systematic Zoology (now
Systematic Biology) in 1983, four years after
Camin's death in 1979. The first four papers on
Caminalcules were written by Robert R. Sokal.
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Assessing tree reliability Phylogenetic
reconstruction is a problem of statistical
inference. One must assess the reliability of the
inferred phylogeny and its component parts.
Questions (1) how reliable is the tree? (2)
which parts of the tree are reliable? (3) is
this tree significantly better than another one?
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Bootstrapping

• A statistical technique that uses intensive
  random resampling of data to estimate a statistic
  whose underlying distribution is unknown.

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Bootstrapping

• Characters are resampled with replacement to
  create many bootstrap replicate data sets
  (pseudosamples)
• Each bootstrap replicate data set is analyzed
• Frequency of occurrence of a group (bootstrap
  proportions) is a measure of support for the group

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Bootstrapping - an example
Partition Table
Ciliate SSUrDNA - parsimony bootstrap
123456789 Freq ----------------- .......
100.00 ....... 100.00 .......
100.00 ..... 100.00 ...
95.50 ....... 84.33 ....
11.83 .... 3.83 ..
2.50 ...... 1.00 ...... 1.00
Ochromonas (1)
Symbiodinium (2)
100
Prorocentrum (3)
Euplotes (8)
84
Tetrahymena (9)
96
Loxodes (4)
100
Tracheloraphis (5)
100
Spirostomum (6)
100
Gruberia (7)
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Reduction of a phylogenetic tree by the
collapsing of internal branches associated with
bootstrap values that are lower than a critical
value (C). (a) Gene tree for a-tubulin (b) C
50 (c) C 90
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Tests for two competing trees

• All these tests use the null hypothesis that the
  differences between two trees (A and B) are no
  greater than expected by chance (from the
  sampling error).

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Likelihood Ratio Test

• Likelihood of Hypothesis 1 L1
• Likelihood of Hypothesis 2 L2
• ? 2(ln L1 ln L2)
• Compare ? to ?2 distributionor to a simulated
  distribution.

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Reliability of Phylogenetic Methods

• Phylogenetic methods can also be evaluated in
  terms of their general performance, particularly
  their
• consistency - approach the truth with more data
• efficiency - how quickly can they handle how much
  data
• robustness - how sensitive to violations of
  assumptions
• Studies of these properties can be analytical or
  by simulation

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Problems with long branches With long branches
most methods may yield erroneous trees. For
example, the maximum-parsimony method tends to
cluster long branches together. This phenomenon
is called long-branch attraction or the
Felsenstein zone
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