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Journal Articles BMC Bioinformatics Year : 2011

Ultra-fast sequence clustering from similarity networks with SiLiX

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.

Dates and versions

hal-00698365 , version 1 (16-05-2012)

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Cite

V. Miele, Simon Penel, L. Duret. Ultra-fast sequence clustering from similarity networks with SiLiX. BMC Bioinformatics, 2011, 12(116), pp.1-9. ⟨10.1186/1471-2105-12-116⟩. ⟨hal-00698365⟩
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