RESUMEN
The Sequence Read Archive (SRA, https://www.ncbi.nlm.nih.gov/sra/) stores raw sequencing data and alignment information to enhance reproducibility and facilitate new discoveries through data analysis. Here we note changes in storage designed to increase access and highlight analyses that augment metadata with taxonomic insight to help users select data. In addition, we present three unanticipated applications of taxonomic analysis.
Asunto(s)
Bacterias/genética , Bases de Datos Genéticas , Metadatos/estadística & datos numéricos , Programas Informáticos , Virus/genética , Bacterias/clasificación , Secuencia de Bases , Secuenciación de Nucleótidos de Alto Rendimiento , Internet , Filogenia , Reproducibilidad de los Resultados , SARS-CoV-2/genética , Análisis de Secuencia de ARN , Virus/clasificaciónRESUMEN
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.