Ultra-fast sequence clustering from similarity networks with SiLiX

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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. © 2011 Miele et al; licensee BioMed Central Ltd.

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APA

Miele, V., Penel, S., & Duret, L. (2011). Ultra-fast sequence clustering from similarity networks with SiLiX. BMC Bioinformatics, 12. https://doi.org/10.1186/1471-2105-12-116

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