Title :

Comparative assessment of long-read error correction software applied to Nanopore RNA-sequencing data

Author(s) :

Lima, Leandro [Auteur correspondant]
Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale [ERABLE]
Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 [LBBE]
Università degli Studi di Roma Tor Vergata [Roma, Italia] = University of Rome Tor Vergata [Rome, Italy] = Université de Rome Tor Vergata [Rome, Italie]
Marchet, Camille [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Caboche, Ségolène [Auteur]
Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 [CIIL]
da Silva, Corinne [Auteur]
Laboratoire de Bioinformatique pour la Génomique et la Biodiversité [LBGB]
Istace, Benjamin [Auteur]
Laboratoire de Bioinformatique pour la Génomique et la Biodiversité [LBGB]
Aury, Jean-Marc [Auteur]
Laboratoire de Bioinformatique pour la Génomique et la Biodiversité [LBGB]
Touzet, Helene [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Chikhi, Rayan [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bioinformatics and Sequence Analysis [BONSAI]

Journal title :

Briefings in Bioinformatics

Pages :

1-18

Publisher :

Oxford University Press (OUP)

Publication date :

2019-06-24

ISSN :

1467-5463

English keyword(s) :

Long reads
RNA-sequencing
Nanopore
Error correction
Benchmark

HAL domain(s) :

Informatique [cs]/Bio-informatique [q-bio.QM]

English abstract : [en]

Motivation: Nanopore long-read sequencing technology offers promising alternatives to high-throughput short read sequencing, especially in the context of RNA-sequencing. However this technology is currently hindered by ...
Show more >Motivation: Nanopore long-read sequencing technology offers promising alternatives to high-throughput short read sequencing, especially in the context of RNA-sequencing. However this technology is currently hindered by high error rates in the output data that affect analyses such as the identification of isoforms, exon boundaries, open reading frames, and the creation of gene catalogues. Due to the novelty of such data, computational methods are still actively being developed and options for the error-correction of Nanopore RNA-sequencing long reads remain limited. Results: In this article, we evaluate the extent to which existing long-read DNA error correction methods are capable of correcting cDNA Nanopore reads. We provide an automatic and extensive benchmark tool that not only reports classical error-correction metrics but also the effect of correction on gene families, isoform diversity, bias towards the major isoform, and splice site detection. We find that long read error-correction tools that were originally developed for DNA are also suitable for the correction of Nanopore RNA-sequencing data, especially in terms of increasing base-pair accuracy. Yet investigators should be warned that the correction process perturbs gene family sizes and isoform diversity. This work provides guidelines on which (or whether) error-correction tools should be used, depending on the application type. Benchmarking software: https://gitlab.com/leoisl/LR_EC_analyser Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.Show less >

Language :

Anglais

Popular science :

Non

ANR Project :

PaRis Artificial Intelligence Research InstitutE
Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs
Signatures transcriptionnelles pour une analyse RNA-seq globale
Algorithmes et outils logiciels pour le séquençage d'ARN de troisième génération

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL