Eoulsan: a cloud computing-based framework facilitating high throughput sequencing analyses

Laurent Jourdren; Maria Bernard; Marie-Agnès Dillies; Stéphane Le Crom

doi:10.1093/bioinformatics/bts165

Eoulsan: a cloud computing-based framework facilitating high throughput sequencing analyses

Bioinformatics. 2012 Jun 1;28(11):1542-3. doi: 10.1093/bioinformatics/bts165. Epub 2012 Apr 5.

Authors

Laurent Jourdren¹, Maria Bernard, Marie-Agnès Dillies, Stéphane Le Crom

Affiliation

¹ École normale supérieure, Institut de Biologie de l'ENS, INSERM U1024, Paris, France. eoulsan@biologie.ens.fr

PMID: 22492314
DOI: 10.1093/bioinformatics/bts165

Abstract

We developed a modular and scalable framework called Eoulsan, based on the Hadoop implementation of the MapReduce algorithm dedicated to high-throughput sequencing data analysis. Eoulsan allows users to easily set up a cloud computing cluster and automate the analysis of several samples at once using various software solutions available. Our tests with Amazon Web Services demonstrated that the computation cost is linear with the number of instances booked as is the running time with the increasing amounts of data.

Availability and implementation: Eoulsan is implemented in Java, supported on Linux systems and distributed under the LGPL License at: http://transcriptome.ens.fr/eoulsan/

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Animals
Computational Biology / methods*
High-Throughput Nucleotide Sequencing / methods*
Mice
Sequence Analysis, RNA / methods*
Software