Do model‐based phylogenetic analyses perform better than parsimony? A test with empirical data

  title={Do model‐based phylogenetic analyses perform better than parsimony? A test with empirical data},
  author={Eirik Rindal and Andrew V. Z. Brower},
The use of model‐based methods to infer a phylogenetic tree from a given data set is frequently motivated by the truism that under certain circumstances the parsimony approach (MP) may produce incorrect topologies, while explicit model‐based approaches are believed to avoid this problem. In the realm of empirical data from actual taxa, it is not known (or knowable) how commonly MP, maximum‐likelihood or Bayesian inference are inaccurate. To test the perceived need for “sophisticated” model… 

Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology

One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model‐based approaches to phylogenetic inference

Efficacy or convenience? Model‐based approaches to phylogeny estimation using morphological data

It is found that although some taxa are shifted back to their “traditional” phylogenetic placement, other clades are disturbed and poor resolution and labile taxa indicate a need for further examination of the morphology and not a change in method.

Homology assessment in parsimony and model‐based analyses: two sides of the same coin

  • Leandro C. S. Assis
  • Biology
    Cladistics : the international journal of the Willi Hennig Society
  • 2015
Although parsimony and model‐based analyses usually achieve concordant topological results, they may generate discordant inferences of character evolution from the same datasets, indicating that method selection has serious implications for evolutionary scenarios and classificatory arrangements.

Comparative evaluation of maximum parsimony and Bayesian phylogenetic reconstruction using empirical morphological data

The results, which were based on a large set of empirical matrices, corroborate recent findings that BI is less precise than MP and show that differences between both approaches were not influenced by increasing sample size.

Statistical Inconsistency of Maximum Parsimony for k-Tuple-Site Data

This work will consider a blockwise approach to alignment analysis, namely the so-called k-tuple analyses, and shows that maximum parsimony is statistically inconsistent for k-Tuple-site data and five taxa.

Parsimony analysis of phylogenomic datasets (I): scripts and guidelines for using TNT (Tree Analysis using New Technology)

The computationally most efficient and versatile parsimony software, TNT, is described, which can be used for phylogenetic and phylogenomic analyses, and a series of scripts that are specifically designed for the analysis of phylogenomic datasets are described.

The jazz of cladistics*

In this metaphorical ‘composition’, nine ‘dissonant chords’ related to the drowning out of cladistic performance are commented on, including the false assumption of the irrelevance of classification and clashes amongst cladists themselves.

Dubious resolution and support from published sparse supermatrices: the importance of thorough tree searches.




Performance of maximum parsimony and likelihood phylogenetics when evolution is heterogeneous

It is shown that maximum likelihood and BMCMC can become strongly biased and statistically inconsistent when the rates at which sequence sites evolve change non-identically over time.

The contest between parsimony and likelihood.

In a “classic” phylogenetic inference problem, the observed taxa are assumed to be the leaves of a bifurcating tree and the goal is to infer just the “topology” of the tree, not amount of time between branching events, or amount of evolution that has taken place on branches, or character states of interior vertices.


The success of 16 methods of phylogenetic inference was examined using consis? tency and simulation analysis. Success?the frequency with which a tree-making method cor? rectly identified the true

Cases in which Parsimony or Compatibility Methods will be Positively Misleading

Parsimony or minimum evolution methods were first introduced into phylogenetic inference by Camin and Sokal (1965), and a number of other parsimony methods have since appeared in the systematic literature and found widespread use in studies of molecular evolution.

Parsimony, likelihood, and simplicity

Parsimony can be justified by very different types of models—either very complex or very simple, which suggests that parsimony does have a unique place among methods of phylogenetic estimation.

Likelihood, parsimony, and heterogeneous evolution.

The authors recommended that results from parsimony, which they consider to be nonparametric, be reported alongside likelihood results, and proposed a mixture model, which was inconsistent but better than either parsimony or standard likelihood under heterotachy.

A review of long‐branch attraction

  • J. Bergsten
  • Biology
    Cladistics : the international journal of the Willi Hennig Society
  • 2005
It is argued that since outgroup taxa almost always represent long branches and are as such a hazard towards misplacing long branched ingroup taxa, phylogenetic analyses should always be run with and without the outgroups included.

Success of Parsimony in the Four‐Taxon Case: Long‐Branch Repulsion by Likelihood in the Farris Zone

The accuracy of phylogenetic methods is reinvestigated for the four‐taxon case with a two‐ edge rate and a three‐edge rate and maximum likelihood methods are shown to be particularly prone to failure when closely related taxa have long branches.

The relative performance of Bayesian and parsimony approaches when sampling characters evolving under homogeneous and heterogeneous sets of parameters

Parsimony was found to be more conservative than Bayesian analyses, in that it resolved fewer incorrect clades and was generally disadvantageous for phylogenetic inference using both parsimony and Bayesian approaches.


Inconsistency of phylogenetic estimations refers to the property of certain estimation methods to converge on the positively wrong estimate with increasing amounts of data. This property, at least