Comparison of Heuristics for Maximum Likelihood Tree Estimation - PowerPoint PPT Presentation

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Comparison of Heuristics for Maximum Likelihood Tree Estimation Milica Hadzi-Tanovic Introduction Phylogeny estimation of evolutionary history is one of the central topics in bioinformatics This project will focus on Maximum

Comparison of Heuristics for Maximum Likelihood Tree Estimation Milica Hadzi-Tanovic
Introduction ● Phylogeny estimation of evolutionary history is one of the central topics in bioinformatics ● This project will focus on Maximum Likelihood (ML) phylogeny estimation
ML Problem Review ● Input: a set sequences of same length S ● Output: a model tree that maximizes the probability of generating the input sequences ● NP-hard ● Statistically consistent ● Software: RAxML, ExaML, FastTree, PhyML, and IQ-TREE
Heuristics Used by Software ● Each method uses some fast technique to get the initial tree and then uses heuristics to optimize them ● FastTree2 uses maximum likelihood nearest-neighbor interchanges (NNI) and minimum-evolution subtree-pruning-regrafting to improve the tree (SPR) ● IQ-TREE combines hill-climbing techniques, random perturbation of current best trees, and a broad sampling of initial starting trees to improve the final tree based on NNI ● RAxML is a parallel algorithm that uses rapid hill-climbing algorithm which is able to infer large trees, also based on NNI
Project Objective ● The goal of this project is to analyze the introduced algorithms in depth and acquire a good understanding of each of them ● Given the literature, I want to understand what each algorithm is doing and see what are the time-accuracy trade offs for each method in the study
Evaluation ● Download and run each ML method examined in the study ● Data set of around 200 sequences from https://pranj.al/mammalian-tutorial.html ● This will help me how long they take and what ML scores I can obtain.
Bibliography ● RAxML Version 8 : A tool for Phylogenetic Analysis and Post-Analysis of Large Phylogenies. A. Stamatakis. Public Library of Science, 2011. ● IQ-TREE : A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. L. Nguyen, H. Schmidt, Arndt von Haeseler, and B. Minh. Mol Biol Evol, 2015. ● FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments. M. Price, P. Dehal, A. Arkin. PLoS One, 2010. ● RAxML and FastTree : Comparing Two Methods for Large-Scale Maximum Likelihood Phylogeny Estimation. K. Liu, R. C. Linder, and Warnow, Tandy. Public Library of Science, 2011.

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