NBC update: The addition of viral and fungal databases to the Naïve Bayes classification tool.
BMC Res Notes
; 5: 81, 2012 Jan 31.
Article
en En
| MEDLINE
| ID: mdl-22293603
ABSTRACT
BACKGROUND:
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.RESULTS:
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.CONCLUSIONS:
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.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
BMC Res Notes
Año:
2012
Tipo del documento:
Article
País de afiliación:
Estados Unidos