STAT: a fast, scalable, MinHash-based k-mer tool to assess Sequence Read Archive next-generation sequence submissions

Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k- mer-based tool for fast assessment of taxonomic diversity intrinsic...

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Veröffentlicht in:	Genome Biology Jg. 22; H. 1; S. 270
Hauptverfasser:	Katz, Kenneth S., Shutov, Oleg, Lapoint, Richard, Kimelman, Michael, Brister, J. Rodney, O’Sullivan, Christopher
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 20.09.2021 Springer Nature B.V BMC
Schlagworte:	Accuracy Animal Genetics and Genomics Archives & records Bioinformatics Biomedical and Life Sciences Biotechnology DNA Contamination Evolutionary Biology genome Genomes High-Throughput Nucleotide Sequencing - methods Human Genetics Humans Life Sciences Metadata Metagenomics Metagenomics - methods Method Microbial Genetics and Genomics MinHash National Center for Biotechnology Information Next-generation sequencing Plant Genetics and Genomics SARS-CoV-2 - genetics Software species diversity Taxonomy MinHash Metagenomics
ISSN:	1474-760X, 1474-7596, 1474-760X
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Abstract	Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k- mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k- mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms.
AbstractList	Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k-mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k-mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms. Abstract Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k-mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k-mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms. Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k- mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k- mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms. Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k-mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k-mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms.Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these submissions. We describe the Sequence Taxonomic Analysis Tool (STAT), a scalable k-mer-based tool for fast assessment of taxonomic diversity intrinsic to submissions, independent of metadata. We show that our MinHash-based k-mer tool is accurate and scalable, offering reliable criteria for efficient selection of data for further analysis by the scientific community, at once validating submissions while also augmenting sample metadata with reliable, searchable, taxonomic terms.
ArticleNumber	270
Author	Katz, Kenneth S. Kimelman, Michael Brister, J. Rodney Lapoint, Richard Shutov, Oleg O’Sullivan, Christopher
Author_xml	– sequence: 1 givenname: Kenneth S. orcidid: 0000-0002-9134-4559 surname: Katz fullname: Katz, Kenneth S. email: kskatz@nih.gov organization: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health – sequence: 2 givenname: Oleg surname: Shutov fullname: Shutov, Oleg organization: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health – sequence: 3 givenname: Richard surname: Lapoint fullname: Lapoint, Richard organization: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health – sequence: 4 givenname: Michael surname: Kimelman fullname: Kimelman, Michael organization: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health – sequence: 5 givenname: J. Rodney surname: Brister fullname: Brister, J. Rodney organization: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health – sequence: 6 givenname: Christopher surname: O’Sullivan fullname: O’Sullivan, Christopher organization: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health
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Snippet	Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these... Abstract Sequence Read Archive submissions to the National Center for Biotechnology Information often lack useful metadata, which limits the utility of these...
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SubjectTerms	Accuracy Animal Genetics and Genomics Archives & records Bioinformatics Biomedical and Life Sciences Biotechnology DNA Contamination Evolutionary Biology genome Genomes High-Throughput Nucleotide Sequencing - methods Human Genetics Humans Life Sciences Metadata Metagenomics Metagenomics - methods Method Microbial Genetics and Genomics MinHash National Center for Biotechnology Information Next-generation sequencing Plant Genetics and Genomics SARS-CoV-2 - genetics Software species diversity Taxonomy
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Title	STAT: a fast, scalable, MinHash-based k-mer tool to assess Sequence Read Archive next-generation sequence submissions
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