Biases in Maximum Likelihood and Parsimony: A Simulation Approach to a 10-Taxon Case

Abstract

Biases present in maximum likelihood and parsimony are investigated through a simulation study in a 10-taxon case in which several long branches coexist with short branches in the modeled topology. The performance of these methods is explored while increasing the length of the long branches with different amounts of data. Also, simulations with different taxonomic sampling schemes are examined through this study. The presence of a strong bias in parsimony is corroborated: the well-known long-branch attraction. Likelihood performance is found to be sensitive to the mere presence extreme of branch length disparity, retrieving topologies compatible with long-branch attraction and long-branch repulsion, irrespective of the correctness of the model used.