Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT
Utrecht University · Universitat de Miguel Hernández d'Elx · +3 more institutions
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…
Citation impact
- FWCI
- 22.13
- Percentile
- 100%
- References
- 49
Authors
5- FAF. A. Bastiaan von MeijenfeldtCorresponding
Utrecht University
- KAKsenia Arkhipova
Utrecht University
- DDDiego D. Cambuy
Utrecht University
- FHFelipe H. Coutinho
Universitat de Miguel Hernández d'Elx, Universidade Federal do Rio de Janeiro, Radboud University Nijmegen, Radboud University Medical Center
- BEBas E. Dutilh
Radboud University Nijmegen, Utrecht University, Radboud University Medical Center
Topics & keywords
- Metagenomics
- Biology
- Biological classification
- Contig
- Genome
- Annotation
- Computational biology
- Taxonomic rank