Title :

SortMeRNA: Fast and accurate filtering of ribosomal RNAs in metatranscriptomic data.

Author(s) :

Kopylova, Evguenia [Auteur correspondant]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Bioinformatics and Sequence Analysis [BONSAI]
Noé, Laurent [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Bioinformatics and Sequence Analysis [BONSAI]
Touzet, Helene [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Bioinformatics and Sequence Analysis [BONSAI]

Journal title :

Bioinformatics

Pages :

3211-3217

Publisher :

Oxford University Press (OUP)

Publication date :

2012-10-15

ISSN :

1367-4803

HAL domain(s) :

Informatique [cs]/Bio-informatique [q-bio.QM]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
Informatique [cs]/Algorithme et structure de données [cs.DS]

English abstract : [en]

MOTIVATION: The application of Next-Generation Sequencing (NGS) technologies to RNAs directly extracted from a community of organisms yields a mixture of fragments characterizing both coding and non-coding types of RNAs. ...
Show more >MOTIVATION: The application of Next-Generation Sequencing (NGS) technologies to RNAs directly extracted from a community of organisms yields a mixture of fragments characterizing both coding and non-coding types of RNAs. The tasks to distinguish among these and to further categorize the families of messenger RNAs and ribosomal RNAs is an important step for examining gene expression patterns of an interactive environment and the phylogenetic classification of the constituting species. RESULTS: We present SortMeRNA, a new software designed to rapidly filter ribosomal RNA fragments from metatranscriptomic data. It is capable of handling large sets of reads and sorting out all fragments matching to the rRNA database with high sensitivity and low running time. AVAILABILITY: http://bioinfo.lifl.fr/RNA/sortmerna CONTACT: evguenia.kopylova@lifl.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Nouvelles approches algorithmiques et bioinformatiques pour l'analyse des grandes masses de données issues des séquenceurs de nouvelle génération.

Collections :

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

Source :

Harvested from HAL