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

Autor:	J. Rodney Brister, Michael Kimelman, Kenneth S. Katz, Oleg Shutov, Richard T. Lapoint, Christopher O'Sullivan
Rok vydání:	2021
Předmět:	Sequence Information retrieval QH301-705.5 SARS-CoV-2 Method High-Throughput Nucleotide Sequencing MinHash QH426-470 DNA Contamination Biology Metadata k-mer Scalability Genetics Humans Metagenomics Biology (General) Software Next generation sequence
Zdroj:	Genome Biology Genome Biology, Vol 22, Iss 1, Pp 1-15 (2021)
ISSN:	1474-760X
Popis:	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. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02490-0.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63dcea8357231f22660d860f265032c3 https://doi.org/10.1186/s13059-021-02490-0 Zobrazit plný text záznamu Full text from SpringerLink