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Mash: fast genome and metagenome distance estimation using MinHash

Genome biology · 2016 · Vol. 17(1) · pp. 132–132
Brian OndovTodd J. TreangenPáll MelstedAdam B. MalloneeNicholas H. BergmanSergey KorenAdam M. Phillippy

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 ).

Genomics and Phylogenetic StudiesMachine Learning in BioinformaticsGene expression and cancer classificationRefSeqMetagenomicsBiologyComputational biologyCluster analysisGenomeNanopore sequencingBioinformaticsGeneticsComputer science

MeSH terms

PhylogenySoftwareCluster AnalysisGenomeEvolution, MolecularGenomicsDatabases, Nucleic AcidMetagenomeMetagenomics

Funding

  • Battelle
  • Science and Technology Directorate
  • National Human Genome Research Institute
Citations
3,435
FWCI
88.08
field-weighted impact
References
59
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100%
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Big Data: Astronomical or Genomical?
PLoS Biology · 2015 · 1,384 citations
A Molecular Phylogeny of Living Primates
PLoS Genetics · 2011 · 1,428 citations
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