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The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical "Microscope" Affect the Biological Interpretation?

Léa Siegwald | Ségolène Caboche | Gaël Even | Eric Viscogliosi | Christophe Audebert | Magali Chabé
Microorganisms | 2019

Targeted metagenomics is the solution of choice to reveal differential microbial profiles (defined by richness, diversity and composition) as part of case-control studies. It is well documented that each data processing step may have the potential to introduce bias in the results. However, selecting a bioinformatics pipeline to analyze high-throughput sequencing data from A to Z remains one of the critical considerations in a case-control microbiota study design. Consequently, the aim of this study was to assess whether the same biological conclusions regarding human gut microbiota composition and diversity could be reached using different bioinformatics pipelines. In this work, we considered four pipelines (mothur, QIIME, kraken and CLARK) with different versions and databases, and examined their impact on the outcome of metagenetic analysis of Ion Torrent 16S sequencing data. We re-analyzed a case-control study evaluating the impact of the colonization of the intestinal protozoa Blastocystis sp. on the human gut microbial profile. Although most pipelines reported the same trends in this case-control study, we demonstrated how the use of different pipelines affects the biological conclusions that can be drawn. Targeted metagenomics must therefore rather be considered as a profiling tool to obtain a broad sense of the variations of the microbiota, rather than an accurate identification tool.

Pubmed ID: 31561435

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Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


Greengenes (tool)

RRID:SCR_002830

Database that provides access to the current and comprehensive 16S rRNA gene sequence alignment for browsing, blasting, probing, and downloading. The data and tools can assist the researcher in choosing phylogenetically specific probes, interpreting microarray results, and aligning/annotating novel sequences. The 16S rRNA gene database provides chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. ARB users can use Greengenes to update local databases.

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RefSeq (tool)

RRID:SCR_003496

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

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SILVA (tool)

RRID:SCR_006423

High quality ribosomal RNA databases providing comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukarya). Supplementary services include a rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. The extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. Alignment tool, SINA, is available for download as well as available for use online.

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QIIME (tool)

RRID:SCR_008249

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.

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DESeq2 (tool)

RRID:SCR_015687

Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.

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