Email updates

Keep up to date with the latest news and content from BMC Evolutionary Biology and BioMed Central.

Open Access Open Badges Methodology article

Accurate and robust phylogeny estimation based on profile distances: a study of the Chlorophyceae (Chlorophyta)

Tobias Müller1*, Sven Rahmann234, Thomas Dandekar1 and Matthias Wolf1

Author Affiliations

1 Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, D-97074 Würzburg, Germany

2 Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestraße 73, D-14195 Berlin, Germany

3 Department of Mathematics and Computer Science, Free University of Berlin, Arnimallee 2–6, D-14195 Berlin, Germany

4 Genome Informatics, Faculty of Technology, University of Bielefeld, D-33594 Bielefeld, Germany

For all author emails, please log on.

BMC Evolutionary Biology 2004, 4:20  doi:10.1186/1471-2148-4-20

Published: 28 June 2004



In phylogenetic analysis we face the problem that several subclade topologies are known or easily inferred and well supported by bootstrap analysis, but basal branching patterns cannot be unambiguously estimated by the usual methods (maximum parsimony (MP), neighbor-joining (NJ), or maximum likelihood (ML)), nor are they well supported. We represent each subclade by a sequence profile and estimate evolutionary distances between profiles to obtain a matrix of distances between subclades.


Our estimator of profile distances generalizes the maximum likelihood estimator of sequence distances. The basal branching pattern can be estimated by any distance-based method, such as neighbor-joining. Our method (profile neighbor-joining, PNJ) then inherits the accuracy and robustness of profiles and the time efficiency of neighbor-joining.


Phylogenetic analysis of Chlorophyceae with traditional methods (MP, NJ, ML and MrBayes) reveals seven well supported subclades, but the methods disagree on the basal branching pattern. The tree reconstructed by our method is better supported and can be confirmed by known morphological characters. Moreover the accuracy is significantly improved as shown by parametric bootstrap.