DOI: 10.1093/bioinformatics/bts611 ISSN:

SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data

Evguenia Kopylova, Laurent Noé, Hélène Touzet
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Molecular Biology
  • Biochemistry
  • Statistics and Probability

Abstract

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 task to distinguish among these and to further categorize the families of messenger RNAs and ribosomal RNAs (rRNAs) 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 rRNA 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.

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