MATAM: reconstruction of phylogenetic ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
MATAM: reconstruction of phylogenetic marker genes from short sequencing reads in metagenomes
Author(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]
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]
Journal title :
Bioinformatics
Pages :
585-591
Publisher :
Oxford University Press (OUP)
Publication date :
2017-10-11
ISSN :
1367-4803
HAL domain(s) :
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Popular science :
Non
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