Automated download and clean-up of family specific databases for kmer-based virus identification

Rosa Lundbye Allesøe*, Camilla Koldbæk Lemvigh, My V T Phan, Philip Thomas Lanken Conradsen Clausen, Alfred Ferrer Florensa, Marion P G Koopmans, Ole Lund, Matthew Cotten

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Here we present an automated pipeline for downloading NCBI GenBank entries (DONE) and continuous updating of a local sequence database based on user-specified queries. The database can be created with either protein or nucleotide sequences containing all entries or complete genomes only.The pipeline can automatically clean the database by removing entries with matches to a database of user-specified sequence contaminants. The default contamination entries include sequences from the UniVec database of plasmids, marker genes and sequencing adapters from NCBI, an E. coli genome, rRNA sequences, vectors and satellite sequences. Furthermore, duplicates are removed and the database is automatically screened for sequences from green fluorescent protein (GFP), luciferase and antibiotic resistance genes that might be present in some GenBank viral entries, and could lead to false positives in virus identification. For utilizing the database we present a useful opportunity for dealing with possible human contamination.We show the applicability of DONE by downloading a virus database comprising 37 virus families. We observed an average increase of 16,776 new entries downloaded per month for the 37 families. Additionally, we demonstrate the utility of a custom database compared to a standard reference database for classifying both simulated and real sequence data. The DONE pipeline for downloading and cleaning is deposited in a publicly available repository (https://bitbucket.org/genomicepidemiology/done/src/master/). Supplementary data are available at Bioinformatics online.
Original languageEnglish
JournalBioinformatics
Volume37
Issue number5
Pages (from-to)705–710
ISSN1367-4811
DOIs
Publication statusPublished - 2021

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