ArticleGenome biology2018
RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification.
Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers.
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Who cites it
109 citing papers in PubMed.
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- Filtering for truth: high-precision taxonomic classification in nanopore shotgun metagenomics data through a KMA-based bioinformatic pipeline (KAPTAIN).BMC genomics · 2026Article
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- Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.npj antimicrobials and resistance · 2025Article
- SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing.Bioinformatics (Oxford, England) · 2025Article
- Precise and scalable metagenomic profiling with sample-tailored minimizer libraries.NAR genomics and bioinformatics · 2025Article
- From air to insight: the evolution of airborne DNA sequencing technologies.Microbiology (Reading, England) · 2025Review
49 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
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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