Luke Sheneman | PubMed Health

PubMed2006

Clearcut: a fast implementation of relaxed neighbor joining.

SUMMARY: Clearcut is an open source implementation for the relaxed neighbor joining (RNJ) algorithm. While traditional neighbor joining (NJ) remains a popular method for distance-based phylogenetic tree reconstruction, it suffers from a O(N(3)) time complexity, where N represents the number of taxa in the input. Due to this steep asymptotic time complexity, NJ cannot reasonably handle very large datasets. In contrast, RNJ realizes a typical-case time complexity on the order of N(2)logN without any significant qualitative difference in output. RNJ is particularly useful when inferring a very large tree or a large number of trees. In addition, RNJ retains the desirable property that it will always reconstruct the true tree given a matrix of additive pairwise distances. Clearcut implements RNJ as a C program, which takes either a set of aligned sequences or a pre-computed distance matrix as input and produces a phylogenetic tree. Alternatively, Clearcut can reconstruct phylogenies using an extremely fast standard NJ implementation. AVAILABILITY: Clearcut source code is available for download at: http://bioinformatics.hungry.com/clearcut

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PubMed2006

Relaxed neighbor joining: a fast distance-based phylogenetic tree construction method.

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.

Algorithms↗