BMC Bioinformatics (Apr 2011)

Ultra-fast sequence clustering from similarity networks with <monospace>SiLiX</monospace>

  • Duret Laurent,
  • Penel Simon,
  • Miele Vincent

DOI
https://doi.org/10.1186/1471-2105-12-116
Journal volume & issue
Vol. 12, no. 1
p. 116

Abstract

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Abstract Background The number of gene sequences that are available for comparative genomics approaches is increasing extremely quickly. A current challenge is to be able to handle this huge amount of sequences in order to build families of homologous sequences in a reasonable time. Results We present the software package SiLiX that implements a novel method which reconsiders single linkage clustering with a graph theoretical approach. A parallel version of the algorithms is also presented. As a demonstration of the ability of our software, we clustered more than 3 millions sequences from about 2 billion BLAST hits in 7 minutes, with a high clustering quality, both in terms of sensitivity and specificity. Conclusions Comparing state-of-the-art software, SiLiX presents the best up-to-date capabilities to face the problem of clustering large collections of sequences. SiLiX is freely available at http://lbbe.univ-lyon1.fr/SiLiX.