title: MMseqs software suite for fast and deep clustering and searching of large protein sequence sets.
abstract: Sequence databases are growing fast, challenging existing analysis pipelines. Reducing the redundancy of sequence databases by similarity clustering improves speed and sensitivity of iterative searches. But existing tools cannot efficiently cluster databases of the size of UniProt to 50% maximum pairwise sequence identity or below. Furthermore, in metagenomics experiments typically large fractions of reads cannot be matched to any known sequence anymore because searching with sensitive but relatively slow tools (e.g. BLAST or HMMER3) through comprehensive databases such as UniProt is becoming too costly.
  
  
  
  MMseqs (Many-against-Many sequence searching) is a software suite for fast and deep clustering and searching of large datasets, such as UniProt, or 6-frame translated metagenomics sequencing reads. MMseqs contains three core modules: a fast and sensitive prefiltering module that sums up the scores of similar k-mers between query and target sequences, an SSE2- and multi-core-parallelized local alignment module, and a clustering module.In our homology detection benchmarks, MMseqs is much more sensitive and 4-30 times faster than UBLAST and RAPsearch, respectively, although it does not reach BLAST sensitivity yet. Using its cascaded clustering workflow, MMseqs can cluster large databases down to ∼30% sequence identity at hundreds of times the speed of BLASTclust and much deeper than CD-HIT and USEARCH. MMseqs can also update a database clustering in linear instead of quadratic time. Its much improved sensitivity-speed trade-off should make MMseqs attractive for a wide range of large-scale sequence analysis tasks.
  
  
  
  MMseqs is open-source software available under GPL at https://github.com/soedinglab/MMseqs
  
  
  
  martin.steinegger@mpibpc.mpg.de, soeding@mpibpc.mpg.de
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Gene Center, Ludwig-Maximilians-Universität München, Munich 81377, Germany.
authors.forename: Maria
authors.initials: M
authors.lastname: Hauser
authors.affiliation: Gene Center, Ludwig-Maximilians-Universität München, Munich 81377, Germany, Computational Biology, Max Planck Institute for Biophysical Chemistry, Göttingen 37077, Germany and TUM, Department of Informatics, Bioinformatics & Computational Biology-I12, Garching 85748, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Steinegger
authors.affiliation: Gene Center, Ludwig-Maximilians-Universität München, Munich 81377, Germany, Computational Biology, Max Planck Institute for Biophysical Chemistry, Göttingen 37077, Germany and.
authors.forename: Johannes
authors.initials: J
authors.lastname: Söding
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D016000:Cluster Analysis; D030561:Databases, Nucleic Acid; D006801:Humans; D056186:Metagenomics; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein; D012984:Software