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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
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author Park, Sang-Cheol
Won, Sungho
author_facet Park, Sang-Cheol
Won, Sungho
author_sort Park, Sang-Cheol
collection PubMed
description 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.
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spelling pubmed-64406772019-04-03 Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community Park, Sang-Cheol Won, Sungho Genomics Inform Original Article 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. Korea Genome Organization 2018-12 2018-12-28 /pmc/articles/PMC6440677/ /pubmed/30602085 http://dx.doi.org/10.5808/GI.2018.16.4.e24 Text en Copyright © 2018 by the Korea Genome Organization It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/).
spellingShingle Original Article
Park, Sang-Cheol
Won, Sungho
Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community
title Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community
title_full Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community
title_fullStr Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community
title_full_unstemmed Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community
title_short Evaluation of 16S rRNA Databases for Taxonomic Assignments Using a Mock Community
title_sort evaluation of 16s rrna databases for taxonomic assignments using a mock community
topic Original Article
url 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
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