title: Eoulsan: a cloud computing-based framework facilitating high throughput sequencing analyses.
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.
  
  
  METHODS
  Eoulsan is implemented in Java, supported on Linux systems and distributed under the LGPL License at: http://transcriptome.ens.fr/eoulsan/
authors.affiliation: École normale supérieure, Institut de Biologie de l'ENS, INSERM U1024, Paris, France. eoulsan@biologie.ens.fr
authors.forename: Laurent
authors.initials: L
authors.lastname: Jourdren
authors.forename: Maria
authors.initials: M
authors.lastname: Bernard
authors.forename: Marie-Agnès
authors.initials: MA
authors.lastname: Dillies
authors.forename: Stéphane
authors.initials: S
authors.lastname: Le Crom
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D051379:Mice; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software