CuReSim-LoRM: A Tool to Simulate Metabarcoding Long Reads.

Mesloub, Yasmina; Beury, Delphine; Vandermeeren, Félix; Caboche, Segolene

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.3390/ijms241814005

PMID :

37762307

URL permanente :

http://hdl.handle.net/20.500.12210/104253

Titre :

CuReSim-LoRM: A Tool to Simulate Metabarcoding Long Reads.

Auteur(s) :

Mesloub, Yasmina [Auteur]
Plateformes Lilloises en Biologie et Santé - UAR 2014 - US 41 [PLBS]
Beury, Delphine [Auteur]
Plateformes Lilloises en Biologie et Santé (PLBS) - UAR 2014 - US 41
Vandermeeren, Félix [Auteur]
Caboche, Segolene [Auteur]

Plateformes Lilloises en Biologie et Santé (PLBS) - UAR 2014 - US 41

Titre de la revue :

International Journal of Molecular Sciences

Nom court de la revue :

Int J Mol Sci

Numéro :

Pagination :

14005

Date de publication :

2023

ISSN :

1422-0067

Mot(s)-clé(s) en anglais :

read simulation
metabarcoding
long reads
benchmark

Discipline(s) HAL :

Statistiques [stat]/Méthodologie [stat.ME]

Résumé en anglais : [en]

Metabarcoding DNA sequencing has revolutionized the study of microbial communities. Third-generation sequencing producing long reads had opened up new perspectives. Obtaining the full-length ribosomal RNA gene would permit ...
Lire la suite >Metabarcoding DNA sequencing has revolutionized the study of microbial communities. Third-generation sequencing producing long reads had opened up new perspectives. Obtaining the full-length ribosomal RNA gene would permit one to reach a better taxonomic resolution at the species or the strain level. However, Oxford Nanopore Technologies (ONT) sequencing produces reads with high error rates, which introduces biases in analysis. Understanding the biases introduced during the analysis allows one to better interpret the biological results and take care of conclusions drawn from metabarcoding experiments. To benchmark an analysis process, the ground truth, i.e., the real composition of the microbial community, has to be known. In addition to artificial mock communities, simulated data are often used to evaluate the biases and performances of the bioinformatics analysis step. Currently, no specific tool has been developed to simulate metabarcoding long reads, mimic the error rate and the length distribution, and allow one to benchmark the analysis process. Here, we introduce CuReSim-LoRM, for the customized read simulator to generate long reads for metabarcoding. We showed that CuReSim-LoRM is able to produce reads with varying error rates and length distributions by mimicking the real data very well.Lire moins >

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Plateformes Lilloises en Biologie et Santé (PLBS) - UAR 2014 - US 41

Date de dépôt :

2024-01-23T22:12:48Z
2024-02-23T21:48:31Z

Fichiers

ijms-24-14005-v2.pdf
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Ce document est diffusé sous licence Attribution 3.0 United States

Numéro de version	Lien	Date de modification
2	20.500.12210/104253*	2024-02-23T21:42:48Z
1	20.500.12210/104253.1	2024-01-23T22:12:48Z

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