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BMCBI
2011

Ultra-fast sequence clustering from similarity networks with SiLiX

8 years 3 months ago
Ultra-fast sequence clustering from similarity networks with SiLiX
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
Vincent Miele, Simon Penel, Laurent Duret
Added 28 May 2011
Updated 28 May 2011
Type Journal
Year 2011
Where BMCBI
Authors Vincent Miele, Simon Penel, Laurent Duret
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