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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
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
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1474-760X
1474-7596
1474-760X
DOI:10.1186/s13059-021-02490-0