Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples.

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State: Public
Version: author
License: CC BY 4.0
Serval ID
serval:BIB_C28685E8F889
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples.
Journal
Frontiers in microbiology
Author(s)
Marizzoni M., Gurry T., Provasi S., Greub G., Lopizzo N., Ribaldi F., Festari C., Mazzelli M., Mombelli E., Salvatore M., Mirabelli P., Franzese M., Soricelli A., Frisoni G.B., Cattaneo A.
ISSN
1664-302X (Print)
ISSN-L
1664-302X
Publication state
Published
Issued date
2020
Peer-reviewed
Oui
Volume
11
Pages
1262
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons across studies difficult. Here, we compared four commonly used pipelines (QIIME2, Bioconductor, UPARSE and mothur) run on two operating systems (OS) (Linux and Mac), to evaluate the impact of bioinformatic pipeline and OS on the taxonomic classification of 40 human stool samples. We applied the SILVA 132 reference database for all the pipelines. We compared phyla and genera identification and relative abundances across the four pipelines using the Friedman rank sum test. QIIME2 and Bioconductor provided identical outputs on Linux and Mac OS, while UPARSE and mothur reported only minimal differences between OS. Taxa assignments were consistent at both phylum and genus level across all the pipelines. However, a difference in terms of relative abundance was identified for all phyla (p < 0.013) and for the majority of the most abundant genera (p < 0.028), such as Bacteroides (QIIME2: 24.5%, Bioconductor: 24.6%, UPARSE-linux: 23.6%, UPARSE-mac: 20.6%, mothur-linux: 22.2%, mothur-mac: 21.6%, p < 0.001). The use of different bioinformatic pipelines affects the estimation of the relative abundance of gut microbial community, indicating that studies using different pipelines cannot be directly compared. A harmonization procedure is needed to move the field forward.
Keywords
16S rRNA amplicon sequencing, QIIME2, UPARSE, bioconductor, fecal human samples, microbiome, mothur
Pubmed
Open Access
Yes
Create date
13/07/2020 12:11
Last modification date
21/07/2023 7:00
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