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Maximum likelihood testing model

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... all possible nucleotides A, G, C, and T occupying nodes (5) and (6), or 4 x 4 ... Protein sequences each site may occupy 20 states (that of the 20 amino acids) ... – PowerPoint PPT presentation

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Title: Maximum likelihood testing model


1
Maximum likelihood testing model
2
Definition
  • Method for the inference of phylogeny
  • Method that searches for the tree with the
    highest probability or likelihood.

3
Advantages of Maximum likelihood
  • Lower variance than other methods
  • Least affected by sampling error
  • Robust to many violations of the assumptions of
    the evolutionary model, even with very short
    sequences, they outperform other methods).
  • Are less error prone.
  • Statistically well founded.
  • Evaluate different tree topologies.

4
Disadvantages of Maximum likelihood
  • CPU intensive and may take a long time to
    complete an evaluation
  • The result is dependent on the model of evolution
    used.

5
Example going through the Maximum likelihood model
  • Assume that we have the aligned nucleotide
    sequences for four taxa
  • (1) A G G C U C C A A ....A
  • (2) A G G U U C G A A ....A
  • (3) A G C C C A G A A.... A
  • A U U U C G G A A.... C
  • Evaluate the likelihood of the uprooted tree
    represented by the nucleotides of site j in the
    sequence

http//www.icp.ucl.ac.be/opperd/private/max_likel
i.html
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  • Since the likelihood of the tree is independent
    of the position of the root, we can display the
    figure as shown in Figure B.
  • Assume that the nucleotides evolve independently
    (the Markovian model of evolution)
  • Calculate the likelihood for each site separately
    and combine the likelihood into a total value
    towards the end.
  • . To calculate the likelihood for site j, we have
    to consider all the possible scenarios by which
    the nucleotides present at the tips of the tree
    could have evolved.
  • Therefore the likelihood for a particular site is
    the summation of the probabilities of every
    possible reconstruction of ancestral states,
    given some model of base substitution.

http//www.icp.ucl.ac.be/opperd/private/max_likel
i.html
7
  • So in this specific case all possible nucleotides
    A, G, C, and T occupying nodes (5) and (6), or 4
    x 4 16 possibilities
  • Protein sequences each site may occupy 20 states
    (that of the 20 amino acids)
  • 20x20 thus 400 possibilities have to be
    considered.
  • Since any one of these scenarios could have led
    to the nucleotide configuration at the tip of the
    tree, we must calculate the probability of each
    and sum them to obtain the total probability for
    each site j.

http//www.icp.ucl.ac.be/opperd/private/max_likel
i.html
8
  • The likelihood for the full tree then is product
    of the likelihood at each site.
  • Since the individual likelihoods are extremely
    small numbers it is convenient to sum the log
    likelihoods at each site and report the
    likelihood of the entire tree as the log
    likelihood.

9
  • This above procedure is then repeated for all
    possible topologies (for all possible trees).
  • The tree with the highest probability is the tree
    with the highest maximum likelihood.
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