4.5 Article

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

Journal

GENOME BIOLOGY
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s13059-021-02490-0

Keywords

Metagenomics; MinHash

Funding

  1. Intramural Research Program of the National Library of Medicine, National Institutes of Health
  2. National Institutes of Health (NIH)

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The study introduces a new tool, STAT, for fast taxonomic diversity assessment of submissions to NCBI, independent of metadata. The tool is accurate, reliable, and scalable, providing a reliable criteria for data selection by the scientific community, while also enhancing the submission metadata with 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.

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