ArticleGenome biology2019
Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 303 papers.
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Who cites it
303 citing papers in PubMed, 569 citations in OpenAlex.
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- Single-contig bacterial genomes recovered from cattle fecal metagenomes at farms with variable antibiotic use.Research square · 2026Article
- Viral Assemblages of a Hypersaline Estuary Show Divergent Responses to Freshwater and Temperature Disturbances.Environmental microbiology reports · 2026Article
- GMW: a hybrid graph-based approach for post-assembly metagenome analysis and decontamination.Science China. Life sciences · 2026Article
- New genomic insights into long-chain alkenone biosynthesis by the coccolithophorid marine alga Gephyrocapsa huxleyi.BMC genomics · 2026Article
- Eco-evolutionary dynamics of massive, parallel bacteriophage outbreaks in compost communities.Science advances · 2026Article
243 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current-day metagenomics analyses increasingly involve de novo taxonomic classification of long DNA sequences and metagenome-assembled genomes. Here, we show that the conventional best-hit approach often leads to classifications that are too specific, especially when the sequences represent novel deep lineages. We present a classification method that integrates multiple signals to classify sequences (Contig Annotation Tool, CAT) and metagenome-assembled genomes (Bin Annotation Tool, BAT). Classifications are automatically made at low taxonomic ranks if closely related organisms are present in the reference database and at higher ranks otherwise. The result is a high classification precision even for sequences from considerably unknown organisms.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.