title: KMC 2: fast and resource-frugal k-mer counting.
abstract: BACKGROUND
  Building the histogram of occurrences of every k-symbol long substring of nucleotide data is a standard step in many bioinformatics applications, known under the name of k-mer counting. Its applications include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. The tremendous amounts of NGS data require fast algorithms for k-mer counting, preferably using moderate amounts of memory.
  
  
  RESULTS
  We present a novel method for k-mer counting, on large datasets about twice faster than the strongest competitors (Jellyfish 2, KMC 1), using about 12 GB (or less) of RAM. Our disk-based method bears some resemblance to MSPKmerCounter, yet replacing the original minimizers with signatures (a carefully selected subset of all minimizers) and using (k, x)-mers allows to significantly reduce the I/O and a highly parallel overall architecture allows to achieve unprecedented processing speeds. For example, KMC 2 counts the 28-mers of a human reads collection with 44-fold coverage (106 GB of compressed size) in about 20 min, on a 6-core Intel i7 PC with an solid-state disk.
authors.affiliation: Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Deorowicz
authors.affiliation: Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.
authors.forename: Marek
authors.initials: M
authors.lastname: Kokot
authors.affiliation: Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.
authors.forename: Szymon
authors.initials: S
authors.lastname: Grabowski
authors.affiliation: Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice and Institute of Applied Computer Science, Lodz University of Technology, Al. Politechniki 11, 90-924 Łódź, Poland.
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Debudaj-Grabysz
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software