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

• Published in: Bioinformatics (Oxford, England) Vol. 28; no. 11; pp. 1542 - 1543
• Main Authors: Jourdren, Laurent, Bernard, Maria, Dillies, Marie-Agnès, Le Crom, Stéphane
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.06.2012; Oxford University Press (OUP)
• Subjects: Algorithms; Animals; Biochemistry, Molecular Biology; Biological and medical sciences; Computational Biology; Computational Biology - methods; Fundamental and applied biological sciences. Psychology; General aspects; Genomics; High-Throughput Nucleotide Sequencing; High-Throughput Nucleotide Sequencing - methods; Life Sciences; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Mice; Quantitative Methods; Sequence Analysis, RNA; Sequence Analysis, RNA - methods; Software; High throughput screening; High throughput sequencing; Computing; Analysis
• ISSN: 1367-4803; 1367-4811; 1367-4811
• DOI: 10.1093/bioinformatics/bts165

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/ Contact:  eoulsan@biologie.ens.fr Supplementary information:  Supplementary data are available at Bioinformatics online.