Mash: Fast genome and metagenome distance estimation using MinHash

  • Brian D. Ondov
  • , Todd J. Treangen
  • , Páll Melsted
  • , Adam B. Mallonee
  • , Nicholas H. Bergman
  • , Sergey Koren
  • , Adam M. Phillippy

Research output: Contribution to journalArticlepeer-review

Abstract

Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license (https://github.com/marbl/mash).

Original languageEnglish
Article number132
JournalGenome Biology
Volume17
Issue number1
DOIs
Publication statusPublished - 20 Jun 2016

Bibliographical note

Publisher Copyright: © 2016 The Author(s).

Other keywords

  • Alignment
  • Comparative genomics
  • Genomic distance
  • Metagenomics
  • Nanopore
  • Sequencing

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