Park Sang-Cheol, Won Sungho
Institute of Health and Environment, Seoul National University, Seoul 08826, Korea.
Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea.
Genomics Inform. 2018 Dec;16(4):e24. doi: 10.5808/GI.2018.16.4.e24. Epub 2018 Dec 28.
Taxonomy identification is fundamental to all microbiology studies. Particularly in metagenomics, which identify 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 showed that EzBioCloud performs well compared to other existing databases.
分类鉴定是所有微生物学研究的基础。尤其是在宏基因组学中,它使用数千个序列来鉴定微生物的组成,其重要性更为突出。鉴定不可避免地会受到数据库选择的影响。本研究旨在评估三个广泛使用的16S数据库(Greengenes、Silva和EzBioCloud)的准确性,并提出选择参考数据库的基本指南。使用公共模拟群落数据,每个数据库都用于进行分类并测试其准确性。我们表明,与其他现有数据库相比,EzBioCloud表现良好。