Mash: fast genome and metagenome distance estimation using MinHash

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 whic...

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Veröffentlicht in:	Genome Biology Jg. 17; H. 1; S. 132
Hauptverfasser:	Ondov, Brian D., Treangen, Todd J., Melsted, Páll, Mallonee, Adam B., Bergman, Nicholas H., Koren, Sergey, Phillippy, Adam M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 20.06.2016 Springer Nature B.V
Schlagworte:	Animal Genetics and Genomics Automation Bioinformatics Biomedical and Life Sciences Cluster Analysis Data collection Databases, Nucleic Acid Estimates Evolution, Molecular Evolutionary Biology Genome Genomes Genomics Genomics - methods Human Genetics Library collections Life Sciences mash Metagenome metagenomics Metagenomics - methods Microbial Genetics and Genomics Mutation nanopores Phylogeny Plant Genetics and Genomics Privacy Software Comparative genomics Metagenomics Alignment Nanopore Genomic distance Sequencing
ISSN:	1474-760X, 1474-7596, 1474-760X
Online-Zugang:	Volltext
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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 ).
AbstractList	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). 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 ). 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 ).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 ).
ArticleNumber	132
Author	Treangen, Todd J. Koren, Sergey Mallonee, Adam B. Melsted, Páll Phillippy, Adam M. Ondov, Brian D. Bergman, Nicholas H.
Author_xml	– sequence: 1 givenname: Brian D. surname: Ondov fullname: Ondov, Brian D. organization: National Biodefense Analysis and Countermeasures Center – sequence: 2 givenname: Todd J. surname: Treangen fullname: Treangen, Todd J. organization: National Biodefense Analysis and Countermeasures Center – sequence: 3 givenname: Páll surname: Melsted fullname: Melsted, Páll organization: Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland – sequence: 4 givenname: Adam B. surname: Mallonee fullname: Mallonee, Adam B. organization: National Biodefense Analysis and Countermeasures Center – sequence: 5 givenname: Nicholas H. surname: Bergman fullname: Bergman, Nicholas H. organization: National Biodefense Analysis and Countermeasures Center – sequence: 6 givenname: Sergey surname: Koren fullname: Koren, Sergey organization: Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health – sequence: 7 givenname: Adam M. surname: Phillippy fullname: Phillippy, Adam M. email: adam.phillippy@nih.gov organization: Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/27323842$$D View this record in MEDLINE/PubMed
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Keywords	Comparative genomics Metagenomics Alignment Nanopore Genomic distance Sequencing
Language	English
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SubjectTerms	Animal Genetics and Genomics Automation Bioinformatics Biomedical and Life Sciences Cluster Analysis Data collection Databases, Nucleic Acid Estimates Evolution, Molecular Evolutionary Biology Genome Genomes Genomics Genomics - methods Human Genetics Library collections Life Sciences mash Metagenome metagenomics Metagenomics - methods Microbial Genetics and Genomics Mutation nanopores Phylogeny Plant Genetics and Genomics Privacy Software
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Title	Mash: fast genome and metagenome distance estimation using MinHash
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