Correcting inconsistencies and errors in bacterial genome metadata using an automated curation tool in Excel (AutoCurE)

Sarah E. Schmedes, Jonathan L. King, Bruce Budowle

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Whole-genome data are invaluable for large-scale comparative genomic studies. Current sequencing technologies have made it feasible to sequence entire bacterial genomes with relative ease and time with a substantially reduced cost per nucleotide, hence cost per genome. More than 3,000 bacterial genomes have been sequenced and are available at the finished status. Publically available genomes can be readily downloaded; however, there are challenges to verify the specific supporting data contained within the download and to identify errors and inconsistencies that may be present within the organizational data content and metadata. AutoCurE, an automated tool for bacterial genome database curation in Excel, was developed to facilitate local database curation of supporting data that accompany downloaded genomes from the National Center for Biotechnology Information. AutoCurE provides an automated approach to curate local genomic databases by flagging inconsistencies or errors by comparing the downloaded supporting data to the genome reports to verify genome name, RefSeq accession numbers, the presence of archaea, BioProject/UIDs, and sequence file descriptions. Flags are generated for nine metadata fields if there are inconsistencies between the downloaded genomes and genomes reports and if erroneous or missing data are evident. AutoCurE is an easy-to-use tool for local database curation for large-scale genome data prior to downstream analyses.

Original languageEnglish
Article number138
JournalFrontiers in Bioengineering and Biotechnology
Volume3
Issue numberSEP
DOIs
StatePublished - 2015

Keywords

  • AutoCurE
  • Automation
  • Bacteria
  • Curation
  • Database
  • Genomes
  • Metadata

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