Goals of Phylogenetic Analysis

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Presentation transcript:

Goals of Phylogenetic Analysis Given a multiple sequence alignment, determine the ancestral relationships among the species. We assume that residues in a column are homologous, and that all columns have the same history. Time Hu Ch Go Gi

Types of Phylogenetic Methods Character-based Parsimony Likelihood Distance-based Neighbor joining (NJ) UPGMA Involve optimizing a criterion based on fit of the residues to the tree. Involve optimizing a criterion based on fit of a matrix of pairwise distances to the tree

Parsimony Select the tree that explains the data with the smallest number of substitutions. Likelihood Select the tree that has the highest probability of producing the observed data Distance Select the tree that best recreates the observed pairwise distances.

We usually estimate unrooted trees B C D A C B D A D C B For 4 sequences, there are only 3 unique unrooted trees.

Parsimony Methods A ACGA B ATGC C GTGC D GCAA A B C D Tree 1 A C B D 1 2 3 4 Tot Tree 1 1 2 1 2 6 Tree 2 2 2 1 2 7 Tree 3 2 1 1 1 5 A D B C Tree 3

is the collection of all data (sequences A, B, and G). Likelihood Methods A B G x is the collection of all parameters affecting the evolution of sequences A, B, and G. is the collection of all data (sequences A, B, and G).

Modeling sequence change Typically, the evolution of DNA sequences is modeled at the level of single sites. JC: Jukes-Cantor (1969) K2P: Kimura (1980) F81: Felsenstein (1981) HKY: Hasegawa et al. (1985) REV: Tavaré (1986)

General Time Reversible Model C G T A C G T

(Nucleotide in Species A, site k) Under this assumption, the likelihood simplifies to a product of individual site likelihoods: and (Nucleotide in Species A, site k) A B G x

Distance Methods A B C D A 0 A ACGA B ATGC B .5 0 C GTGC C .75 .25 0 D GCAA

A B C D a c e b d Many distance methods seek to find the tree that minimizes a score such as: