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

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Accès restreint UNIL
Etat: Public
Version: de l'auteur⸱e
Licence: CC BY 4.0
ID Serval
serval:BIB_C28685E8F889
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples.
Périodique
Frontiers in microbiology
Auteur⸱e⸱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
Statut éditorial
Publié
Date de publication
2020
Peer-reviewed
Oui
Volume
11
Pages
1262
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
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.
Mots-clé
16S rRNA amplicon sequencing, QIIME2, UPARSE, bioconductor, fecal human samples, microbiome, mothur
Pubmed
Open Access
Oui
Création de la notice
13/07/2020 12:11
Dernière modification de la notice
21/07/2023 7:00
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