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Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community

Taxonomic identification is fundamental to all microbiology studies. Particularly in metagenomics, which identifies the composition of microorganisms using thousands of sequences, its importance is even greater. Identification is inevitably affected by the choice of database. This study was conducte...

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Detalles Bibliográficos
Autores principales: Park, Sang-Cheol, Won, Sungho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6440677/
https://www.ncbi.nlm.nih.gov/pubmed/30602085
http://dx.doi.org/10.5808/GI.2018.16.4.e24
Descripción
Sumario:Taxonomic identification is fundamental to all microbiology studies. Particularly in metagenomics, which identifies the composition of microorganisms using thousands of sequences, its importance is even greater. Identification is inevitably affected by the choice of database. This study was conducted to evaluate the accuracy of three widely used 16S databases—Greengenes, Silva, and EzBioCloud—and to suggest basic guidelines for selecting reference databases. Using public mock community data, each database was used to assign taxonomy and to test its accuracy. We show that EzBioCloud performs well compared with other existing databases.