PT  - JOURNAL ARTICLE
AU  - Joseph W. Brown
AU  - Caroline Parins-Fukuchi
AU  - Gregory W. Stull
AU  - Oscar M. Vargas
AU  - Stephen A. Smith
TI  - Missing the point (estimate): Bayesian and likelihood phylogenetic reconstructions of morphological characters produce generally concordant inferences. A comment on
AID  - 10.1101/114793
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 114793
4099  - http://biorxiv.org/content/early/2017/03/16/114793.1.short
4100  - http://biorxiv.org/content/early/2017/03/16/114793.1.full
AB  - Puttick et al. (2017) performed a simulation study to compare accuracy between methods inferring phylogeny from discrete morphological characters. They report that a Bayesian implementation of the Mk model (Lewis, 2001) was most accurate (but with low resolution), while a maximum likelihood (ML) implementation of the same model was least accurate. They conclude by strongly advocating that Bayesian implementations of the Mk model should be the default method of analysis for such data. While we applaud investigations into accuracy and alternative methods of analysis, this conclusion is based on an inappropriate comparison of the ML point estimate with the Bayesian consensus. We revisit these issues through simulation by considering uncertainty in ML reconstructions, and demonstrate that Bayesian and ML estimates are generally concordant when conventional edge support thresholds are considered. We therefore disagree with the conclusions of Puttick et al. (2017), and consider their prescription of any default method to be unfounded. Instead, we recommend caution and thoughtful consideration of the model or method being applied to a morphological dataset.