RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification

Abstract

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.

Keywords

• Taxonomic classification
• Reference database
• Metagenomics
• Microbiome
• Comparative analysis
• k-mer