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

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Vincent Miele, Simon Penel, Laurent Duret
• Keywords: Artificial Intelligence, BMCBI 2011, Graph Theoretical Approach, Sequences, Software Package Silix