Table of ContentsEvolutionary Trees The problem: PPT Slide PPT Slide Terminology PPT Slide PPT Slide Biological Assumptions Character Homology Bifurcating descent PPT Slide Estimation Principles Distance relationships PPT Slide PPT Slide PPT Slide Nested character-states PPT Slide PPT Slide PPT Slide Likelihood Suppose we see “AAAT”, what is the probability of drawing a base “A”? Markov chain model of character evolution Transition probability is specified from node to node The character evolution model is determined by the form of the constraints on the transition matrix The model is specified by the branching order of the tree, the initial state at the common ancestor, and a transition matrix for each branch Given the model, the probability of any character pattern at the tips of the tree can be computed For t number of taxa and n-state characters there are nt number of character patterns at the tips of the tree PPT Slide Algorithmic Structure Optimization Combinatorial Optimization PPT Slide Number of possible unrooted binary trees with n-taxa PPT Slide PPT Slide PPT Slide Solutions Exhaustive search Branch-and-bound search PPT Slide Divide-and-conquer PPT Slide Dynamic Programming PPT Slide PPT Slide Heuristics Greedy search Stochastic search Simulated annealing Super-duper clever search Heuristic solutions are dependent on ... PPT Slide Neighbor relations of trees NNI configuration TBR Configuration PPT Slide Statistical Properties PPT Slide Accuracy is some measurement of the dispersal of the estimator distribution around the “true” value “?????”???We need a way of measuring deviation between trees Partition metric Consensus Majority-rule consensus Consensus tree can be used to define a deviation measure Tree neighbor relations can be used to define deviation PPT Slide Power and Error Power, Error, and Accuracy are not necessarily related to each other Confidence Limits PPT Slide PPT Slide Bootstrap resampling as a means of generating replicate samples (step 2) Majority-rule consensus trees can be used to select confidence sets (step 4) Misc. confidence limites |
Author: Junhyong Kim
Home Page: http://bioinfo.mbb.yale.edu/course |