Pitfalls of the site-concordance factor (sCF) as measure of phylogenetic branch support

Author:

Kück Patrick1ORCID,Romahn Juliane123,Meusemann Karen4

Affiliation:

1. Centre for Molecular Biodiversity Research, Leibniz Institute for the Analysis of Biodiversity Change , Adenauerallee 160, 53113 Bonn, Germany

2. LOEWE Centre for Translational Biodiversity Genomics (LOEWE-TBG) , Senckenberganlage 25, 60325 Frankfurt am Main, Germany

3. Senckenberg Society for Nature Research , Senckenberganlage 25, 60325 Frankfurt am Main, Germany

4. Directorate, Leibniz Institute for the Analysis of Biodiversity Change , Adenauerallee 160, 53113 Bonn, Germany

Abstract

Abstract Confidence measures of branch reliability play an important role in phylogenetics as these measures allow to identify trees or parts of a tree that are well supported by the data and thus adequate to serve as basis for evolutionary inference of biological systems. Unreliable branch relationships in phylogenetic analyses are of concern because of their potential to represent incorrect relationships of interest among more reliable branch relationships. The site-concordance factor implemented in the IQ-TREE package is a recently introduced heuristic solution to the problem of identifying unreliable branch relationships on the basis of quartets. We test the performance of the site-concordance measure with simple examples based on simulated data and designed to study its behaviour in branch support estimates related to different degrees of branch length heterogeneities among a ten sequence tree. Our results show that in particular in cases of relationships with heterogeneous branch lengths site-concordance measures may be misleading. We therefore argue that the maximum parsimony optimality criterion currently used by the site-concordance measure may sometimes be poorly suited to evaluate branch support and that the scores reported by the site-concordance factor should not be considered as reliable.

Funder

LIB

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computer Science Applications,Genetics,Molecular Biology,Structural Biology

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