Evidence map›Paper›PMID 33129268›Full record

ArticleBMC bioinformatics2020

BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons.

Christophe Djemiel, Samuel Dequiedt, Battle Karimi, Aurélien Cottin, Thibault Girier, Yassin El Djoudi, Patrick Wincker, Mélanie Lelièvre, Samuel Mondy, Nicolas Chemidlin Prévost-Bouré and 3 more

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

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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

13 authors.

Christophe DjemielAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.ORCID http://orcid.org/0000-0002-5659-7876
Samuel DequiedtAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.
Battle KarimiAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.ORCID http://orcid.org/0000-0002-4523-974X
Aurélien CottinAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.ORCID http://orcid.org/0000-0002-0862-784X
Thibault GirierAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.
Yassin El DjoudiAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.
Patrick WinckerCEA/Institut de Biologie François Jacob/Génoscope, 2, Rue Gaston Crémieux, CP5706, 91057, Evry Cedex, France.
Mélanie LelièvreAgroécologie - Plateforme GenoSol, BP 86510, 21000, Dijon, France.
Samuel MondyAgroécologie - Plateforme GenoSol, BP 86510, 21000, Dijon, France.ORCID http://orcid.org/0000-0002-9203-6398
Nicolas Chemidlin Prévost-BouréAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.ORCID http://orcid.org/0000-0002-8575-4295
Pierre-Alain MaronAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.
Lionel RanjardAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France.ORCID http://orcid.org/0000-0002-7720-5843
Sébastien TerratAgroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France. sebastien.terrat@inrae.fr.ORCID http://orcid.org/0000-0001-5209-6196

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ability to compare samples or studies easily using metabarcoding so as to better interpret microbial ecology results is an upcoming challenge. A growing number of metabarcoding pipelines are available, each with its own benefits and limitations. However, very few have been developed to offer the opportunity to characterize various microbial communities (e.g., archaea, bacteria, fungi, photosynthetic microeukaryotes) with the same tool.

resultsBIOCOM-PIPE is a flexible and independent suite of tools for processing data from high-throughput sequencing technologies, Roche 454 and Illumina platforms, and focused on the diversity of archaeal, bacterial, fungal, and photosynthetic microeukaryote amplicons. Various original methods were implemented in BIOCOM-PIPE to (1) remove chimeras based on read abundance, (2) align sequences with structure-based alignments of RNA homologs using covariance models, and (3) a post-clustering tool (ReClustOR) to improve OTUs consistency based on a reference OTU database. The comparison with two other pipelines (FROGS and mothur) and Amplicon Sequence Variant definition highlighted that BIOCOM-PIPE was better at discriminating land use groups.

conclusionsThe BIOCOM-PIPE pipeline makes it possible to analyze 16S, 18S and 23S rRNA genes in the same packaged tool. The new post-clustering approach defines a biological database from previously analyzed samples and performs post-clustering of reads with this reference database by using open-reference clustering. This makes it easier to compare projects from various sequencing runs, and increased the congruence among results. For all users, the pipeline was developed to allow for adding or modifying the components, the databases and the bioinformatics tools easily, giving high modularity for each analysis.

Indexed as

BiodiversityDNA Barcoding, TaxonomicGenes, rRNASoftwareArchaeaBacteriaCluster AnalysisComputational BiologyComputer SimulationDatabases, GeneticFungiMicrobiotaRNA, Ribosomal, 16SRNA, Ribosomal, 23SSoil MicrobiologyRNA, Ribosomal, 16SRNA, Ribosomal, 23SArchaealBacterialEcologyFranceFungalLand-useMetabarcodingPhotosynthetic microeukaryotesReClustOR

Identifiers

PMID33129268
PMCPMC7603665

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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.