Evaluation of the Relative Performance of the Subflattenings Method for Phylogenetic Inference

Author:

Stevenson JoshuaORCID,Holland BarbaraORCID,Charleston Michael,Sumner Jeremy

Abstract

AbstractThe algebraic properties offlatteningsandsubflatteningsprovide direct methods for identifying edges in the true phylogeny—and by extension the complete tree—using pattern counts from a sequence alignment. The relatively small number of possible internal edges among a set of taxa (compared to the number of binary trees) makes these methods attractive; however, more could be done to evaluate their effectiveness for inferring phylogenetic trees. This is the case particularly for subflattenings, and the work we present here makes progress in this area. We introduce software for constructing and evaluating subflattenings for splits, utilising a number of methods to make computing subflattenings more tractable. We then present the results of simulations we have performed in order to compare the effectiveness of subflattenings to that of flattenings in terms of split score distributions, and susceptibility to possible biases. We find that subflattenings perform similarly to flattenings in terms of the distribution of split scores on the trees we examined, but may be less affected by bias arising from both split size/balance and long branch attraction. These insights are useful for developing effective algorithms to utilise these tools for the purpose of inferring phylogenetic trees.

Funder

Australian Government RTP Scholarship

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,General Agricultural and Biological Sciences,Pharmacology,General Environmental Science,General Biochemistry, Genetics and Molecular Biology,General Mathematics,Immunology,General Neuroscience

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