Automated Plausibility Analysis of Large Phylogenies

• Published in: Pattern Recognition in Computational Molecular Biology pp. 457 - 482
• Main Authors: Dao, David, Flouri, Tomáš, Stamatakis, Alexandros
• Format: Book Chapter
• Language: English
• Published: Hoboken, NJ, USA John Wiley & Sons, Inc 19.11.2015
• Subjects: automated plausibility analysis; large phylogenies; lowest common ancestor; naive approach; plausibility‐check algorithm
• ISBN: 9781118893685; 1118893689
• DOI: 10.1002/9781119078845.ch24

This chapter introduces a new approach to assess the plausibility of large phylogenies by computing all pairwise topological Robinson‐Foulds (RF) distances of a 55,000 taxon tree of plants, for instance, and a set containing a large number of substantially smaller reference trees. It first presents a naive and then an effective algorithm for inducing subtrees. The chapter then provides an experimental evaluation of both algorithms using simulated and real data from STBase. The chapter describes a novel method for speeding up the computation of induced subtrees from a given leaf set. The key idea is to root the large tree at an inner node and compute the lowest common ancestor (LCA) of each and every pair of leaves in the leaf set. Finally, the chapter presents a straightforward implementation of the plausibility‐check algorithm. The authors have implemented the algorithm in C as part of RAxML.