RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification
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Abstract In order to determine the role of the database in taxonomic sequence classification, we examine the influence of the database over time on k-mer-based lowest common ancestor taxonomic classification. We present three major findings: the number of new species added to the NCBI RefSeq database greatly outpaces the number of new genera; as a result, more reads are classified with newer database versions, but fewer are classified at the species level; and Bayesian-based re-estimation mitigates this effect but struggles with novel genomes. These results suggest a need for new classification approaches specially adapted for large databases.
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Nasko, Daniel J, Koren, Sergey, Phillippy, Adam M, et al.. "RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification." (2018) BioMed Central: https://doi.org/10.1186/s13059-018-1554-6.