The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community
There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comp...
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doaj-da6f2ea0e08a48ba839d23aca3efad162020-11-25T02:55:12ZengMDPI AGGenes2073-44252020-08-011187887810.3390/genes11080878The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial CommunityMaria A. Sierra0Qianhao Li1Smruti Pushalkar2Bidisha Paul3Tito A Sandoval4Angela R. Kamer5Patricia Corby6Yuqi Guo7Ryan Richard Ruff8Alexander V. Alekseyenko9Xin Li10Deepak Saxena11Department of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY 10065, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Epidemiology & Health Promotion, New York University College of Dentistry, New York, NY 10010, USAThe Biomedical Informatics Center, Program for Human Microbiome Research, Department of Public Health Sciences, Department of Oral Health Sciences, Department of Healthcare Leadership and Management, Medical University of South Carolina, Charleston, SC 29425, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USADepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USAThere is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as <i>Veillonella</i>, <i>Rothia</i>, and <i>Prevotella</i>, are annotated by all databases; however, less common genera, such as <i>Bulleidia</i> and <i>Paludibacter</i>, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies.https://www.mdpi.com/2073-4425/11/8/87816S rRNAdatabasesGreengenesHOMDNCBISILVA |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maria A. Sierra Qianhao Li Smruti Pushalkar Bidisha Paul Tito A Sandoval Angela R. Kamer Patricia Corby Yuqi Guo Ryan Richard Ruff Alexander V. Alekseyenko Xin Li Deepak Saxena |
spellingShingle |
Maria A. Sierra Qianhao Li Smruti Pushalkar Bidisha Paul Tito A Sandoval Angela R. Kamer Patricia Corby Yuqi Guo Ryan Richard Ruff Alexander V. Alekseyenko Xin Li Deepak Saxena The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community Genes 16S rRNA databases Greengenes HOMD NCBI SILVA |
author_facet |
Maria A. Sierra Qianhao Li Smruti Pushalkar Bidisha Paul Tito A Sandoval Angela R. Kamer Patricia Corby Yuqi Guo Ryan Richard Ruff Alexander V. Alekseyenko Xin Li Deepak Saxena |
author_sort |
Maria A. Sierra |
title |
The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community |
title_short |
The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community |
title_full |
The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community |
title_fullStr |
The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community |
title_full_unstemmed |
The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community |
title_sort |
influences of bioinformatics tools and reference databases in analyzing the human oral microbial community |
publisher |
MDPI AG |
series |
Genes |
issn |
2073-4425 |
publishDate |
2020-08-01 |
description |
There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as <i>Veillonella</i>, <i>Rothia</i>, and <i>Prevotella</i>, are annotated by all databases; however, less common genera, such as <i>Bulleidia</i> and <i>Paludibacter</i>, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies. |
topic |
16S rRNA databases Greengenes HOMD NCBI SILVA |
url |
https://www.mdpi.com/2073-4425/11/8/878 |
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