Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT

By F. V. Meijenfeldt, K. Arkhipova, Diego Duque Cambuy, Felipe Hernandes Coutinho, Bas E. Dutilh. Genome Biology, 2019

483 citations recorded by the source corpus.

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.

Subfields: Food Science, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/8f975cffe4f396c7905d095cddb0472e3ac331b7

Citations in the corpus

• Effect of ammonia on anaerobic digestion of municipal solid waste: Inhibitory performance, bioaugmentation and microbiome functional reconstruction (2020, unknown): “GTDB-Tk [40] and CAT [41] provided taxonomical assignment and functional analysis.”