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NBC update: The addition of viral and fungal databases to the Naïve Bayes classification tool
Journal article   Open access   Peer reviewed

NBC update: The addition of viral and fungal databases to the Naïve Bayes classification tool

Gail L Rosen and Tze Yee Lim
BMC research notes, v 5(1), pp 81-81
31 Jan 2012
DOI: https://doi.org/10.1186/1756-0500-5-81
PMID: 22293603
url
https://doi.org/10.1186/1756-0500-5-81View
Published, Version of Record (VoR) Open

Abstract

Classifying 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. We 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. In 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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