Journal of Molecular Evolution

, Volume 62, Issue 6, pp 785–792 | Cite as

Relaxed Neighbor Joining: A Fast Distance-Based Phylogenetic Tree Construction Method

  • Jason EvansEmail author
  • Luke Sheneman
  • James Foster


Our ability to construct very large phylogenetic trees is becoming more important as vast amounts of sequence data are becoming readily available. Neighbor joining (NJ) is a widely used distance-based phylogenetic tree construction method that has historically been considered fast, but it is prohibitively slow for building trees from increasingly large datasets. We developed a fast variant of NJ called relaxed neighbor joining (RNJ) and performed experiments to measure the speed improvement over NJ. Since repeated runs of the RNJ algorithm generate a superset of the trees that repeated NJ runs generate, we also assessed tree quality. RNJ is dramatically faster than NJ, and the quality of resulting trees is very similar for the two algorithms. The results indicate that RNJ is a reasonable alternative to NJ and that it is especially well suited for uses that involve large numbers of taxa or highly repetitive procedures such as bootstrapping.


Phylogenetic tree construction Neighbor joining Distance method 



The authors thank Paul Joyce and Holly Wichman for their suggestions regarding experimental design, Bryan Carstens, Jack Sullivan, the students in the spring 2005 systematic biology course at the University of Idaho, and two anonymous reviewers for their review comments, and Bernard Moret for discussions regarding distance metrics. Evans and Foster were partially funded by NIH NCRR 1P20 RR16448. Sheneman was partially funded by NIH P20 RR16454 from the INBRE Program of the National Center for Research Resources. Some of the experiments were run on the IBEST Beowulf cluster, which is funded in part by NSF EPS 00809035, NIH NCRR 1P20 RR16448, and NIH NCRR 1P20 RR16454.


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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Department of Biological SciencesUniversity of IdahoMoscowUSA

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