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Updated: Jun 2, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
Ultra-fast sequence clustering from similarity networks with SiLiX
Vincent Miele1, Simon Penel, Laurent Duret
1Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRIA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr
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.
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