QuickTree: building huge Neighbour-Joining trees of protein sequences.

The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK.
Bioinformatics (Impact Factor: 4.62). 12/2002; 18(11):1546-7. DOI: 10.1093/bioinformatics/18.11.1546
Source: PubMed

ABSTRACT We have written a fast implementation of the popular Neighbor-Joining tree building algorithm. QuickTree allows the reconstruction of phylogenies for very large protein families (including the largest Pfam alignment containing 27000 HIV GP120 glycoprotein sequences) that would be infeasible using other popular methods.

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    ABSTRACT: Phylogenetic methods are becoming part of the standard method-ologies used in the analyses of biological sequence data, but several of the classical tools of phylogenetic inference were not designed with high throughput applications in mind. During our surveys, we haven't found software for the fast inference of neighbor joining trees from sequence alignments which could use biologically realistic substitution models with protein alignments. Thus, we developed quicktree-sd based on an ecient implementation of the neighbor joining algorithm by [3], by implementing an amino acid distance correction based on Scoredist distances. The tool is available at High throughput phylogenetic inference is being used to an increasing extent in the context of genomic data. On the one hand, phylogenetic methods are used to improve genome annotation [1],[2]; on the other, genomic data are used in order to understand evolutionary / phylogenetic questions [4]. One of the simpler methods of phylogenetic inference is neighbor joining (NJ; [5]), which provides a good compromise between computational requirements and accuracy, provided that biologically realistic substitution models are used for estimating distances between sequences [7]. Surprisingly, we have not found any available tool for constructing NJ trees from sequence alignments combining performance with a biologically realistic amino acid substitution model. Quicktree [3] was developed as a tool for the fast inference of NJ trees, with high throughput applications in mind. However, the original implementation of Quicktree did not use an amino acid substitution matrix for calculating the dis-tance matrices. Scoredist was proposed as a simple and generally usable protein sequence distance estimator by [6]. We implemented this distance estimator in quicktree and provide the tool for the scientic community as source code and binaries at (also see
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    ABSTRACT: Phylogenetic analysis is a critical area of modern life biology, and is among the most computationally intensive areas of the life sciences. Phylogenetics, the study of evolutionary relationships, is used to study a wider range of topics, including the evolution of critical traits, speciation, adaptation, and many other areas. In this paper, we present an implementation of a scal-able approach to the construction of phylogenetic trees, derived from the neighbor joining algorithm for tree construction, and specifically upon the optimizations to this algorithm implemented in the NINJA software. Performance results and an analysis of the scalability of this approach is presented.

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