Titre :

MATAM: reconstruction of phylogenetic marker genes from short sequencing reads in metagenomes

Auteur(s) :

Pericard, Pierre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bioinformatics and Sequence Analysis [BONSAI]
Dufresne, Yoann [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bioinformatics and Sequence Analysis [BONSAI]
Couderc, Loïc [Auteur]
Plateforme de bioinformatique et de biostatistique de Lille - PLBS [Bilille]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Blanquart, Samuel [Auteur]
Bioinformatics and Sequence Analysis [BONSAI]
Touzet, Helene [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bioinformatics and Sequence Analysis [BONSAI]

Titre de la revue :

Bioinformatics

Pagination :

585-591

Éditeur :

Oxford University Press (OUP)

Date de publication :

2017-10-11

ISSN :

1367-4803

Discipline(s) HAL :

Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]

Résumé en anglais : [en]

Motivation: Advances in the sequencing of uncultured environmental samples, dubbed metagenomics, raise a growing need for accurate taxonomic assignment. Accurate identification of organisms present within a community is ...
Lire la suite >Motivation: Advances in the sequencing of uncultured environmental samples, dubbed metagenomics, raise a growing need for accurate taxonomic assignment. Accurate identification of organisms present within a community is essential to understanding even the most elementary ecosystems. However, current high-throughput sequencing technologies generate short reads which partially cover full-length marker genes and this poses difficult bioinformatic challenges for taxonomy identification at high resolution. Results: We designed MATAM, a software dedicated to the fast and accurate targeted assembly of short reads sequenced from a genomic marker of interest. The method implements a stepwise process based on construction and analysis of a read overlap graph. It is applied to the assembly of 16S rRNA markers and is validated on simulated, synthetic and genuine metagenomes. We show that MATAM outperforms other available methods in terms of low error rates and recovered fractions and is suitable to provide improved assemblies for precise taxonomic assignments.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL