The khmer software package: Enabling efficient nucleotide sequence analysis

C. Titus Brown, Michael R. Crusoe, Hussien F. Alameldin, Sherine Awad, Elmar Boucher, Adam Caldwell, Reed Cartwright, Amanda Charbonneau, Bede Constantinides, Greg Edvenson, Scott Fay, Jacob Fenton, Thomas Fenzl, Jordan Fish, Leonor Garcia-Gutierrez, Phillip Garland, Jonathan Gluck, Iván González, Sarah Guermond, Jiarong GuoAditi Gupta, Joshua R. Herr, Adina Howe, Alex Hyer, Andreas Härpfer, Luiz Irber, Rhys Kidd, David Lin, Justin Lippi, Tamer Mansour, Pamela McA'Nulty, Eric McDonald, Jessica Mizzi, Kevin D. Murray, Joshua R. Nahum, Kaben Nanlohy, Alexander Johan Nederbragt, Humberto Ortiz-Zuazaga, Jeramia Ory, Jason Pell, Charles Pepe-Ranney, Zachary N. Russ, Erich Schwarz, Camille Scott, Josiah Seaman, Scott Sievert, Jared Simpson, Connor T. Skennerton, James Spencer, Ramakrishnan Srinivasan, Daniel Standage, James A. Stapleton, Susan R. Steinman, Joe Stein, Benjamin Taylor, Will Trimble, Heather L. Wiencko, Michael Wright, Brian Wyss, Qingpeng Zhang, En Zyme

Research output: Contribution to journalArticlepeer-review

156 Scopus citations

Abstract

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/.

Original languageEnglish (US)
Article number900
JournalF1000Research
Volume4
DOIs
StatePublished - 2015

Keywords

  • Bioinformatics
  • Dna sequencing analysis
  • K-mer
  • Khmer
  • Kmer
  • Low-memory
  • Online
  • Streaming

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Pharmacology, Toxicology and Pharmaceutics(all)

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