ArticleBMC research notes2012
NBC update: The addition of viral and fungal databases to the Naïve Bayes classification tool.
Article in BMC research notes, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Machine Learning and Deep Learning Applications in Metagenomic Taxonomy and Functional Annotation.Frontiers in microbiology · 2022Review
- Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.Genome biology · 2017Article
- Protein signature-based estimation of metagenomic abundances including all domains of life and viruses.Bioinformatics (Oxford, England) · 2013Article
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Authors and funding
2 authors.
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Abstract
backgroundClassifying the fungal and viral content of a sample is an important component of analyzing microbial communities in environmental media. Therefore, a method to classify any fragment from these organisms' DNA should be implemented.
resultsWe update the näive Bayes classification (NBC) tool to classify reads originating from viral and fungal organisms. NBC classifies a fungal dataset similarly to Basic Local Alignment Search Tool (BLAST) and the Ribosomal Database Project (RDP) classifier. We also show NBC's similarities and differences to RDP on a fungal large subunit (LSU) ribosomal DNA dataset. For viruses in the training database, strain classification accuracy is 98%, while for those reads originating from sequences not in the database, the order-level accuracy is 78%, where order indicates the taxonomic level in the tree of life.
conclusionsIn addition to being competitive to other classifiers available, NBC has the potential to handle reads originating from any location in the genome. We recommend using the Bacteria/Archaea, Fungal, and Virus databases separately due to algorithmic biases towards long genomes. The tool is publicly available at: http://nbc.ece.drexel.edu.
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Registered trials
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