title: 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.
authors.affiliation: Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRIA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr
authors.forename: Vincent
authors.initials: V
authors.lastname: Miele
authors.forename: Simon
authors.initials: S
authors.lastname: Penel
authors.forename: Laurent
authors.initials: L
authors.lastname: Duret
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D016000:Cluster Analysis; D030541:Databases, Genetic; D050259:Genes, Mitochondrial; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software