Evidence map›Paper›PMID 32756341›Full record

ArticleGenes2020

The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community.

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 and 2 more

Abstract readComparative Study
In one paragraph

Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Maria A SierraDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.ORCID 0000-0003-4115-034X
Qianhao LiDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.
Smruti PushalkarDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.ORCID 0000-0001-7215-0671
Bidisha PaulDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.
Tito A SandovalDepartment of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY 10065, USA.
Angela R KamerDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.
Patricia CorbyDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.
Yuqi GuoDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.
Ryan Richard RuffDepartment of Epidemiology & Health Promotion, New York University College of Dentistry, New York, NY 10010, USA.
Alexander V AlekseyenkoThe 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, USA.
Xin LiDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.ORCID 0000-0002-7414-5734
Deepak SaxenaDepartment of Basic Science, New York University College of Dentistry, New York, NY 10010, USA.

Funding

Distance-based Panomic Analytics for Microbiome DataR01LM012517 · NLM · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ALEKSEYENKO, ALEXANDER V · 2018 to 2021
$1.3M
NIH HHS CA206105NIH HHS DE025992NIH HHS DE027074NLM NIH HHS R01 LM012517
6 · The paper itself

Abstract

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

Indexed as

MicrobiotaComputational BiologyDatabases, GeneticDNA Barcoding, TaxonomicHumansMouthRNA, Ribosomal, 16SRNA, Ribosomal, 16S16S rRNADADA2databasesGreengenesHOMDNCBIQIIMERDPSILVA

Identifiers

PMID32756341
PMCPMC7465726

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.