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

Laurent Jourdren | Zendy; Maria Bernard | Zendy; MarieAgnès Dillies | Zendy; Stéphane Le Crom | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

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

Author(s) -

Laurent Jourdren,

Maria Bernard,

MarieAgnès Dillies,

Stéphane Le Crom

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts165

Subject(s) - computer science , cloud computing , scalability , throughput , java , software , distributed computing , operating system , mit license , license , modular design , set (abstract data type) , big data , data mining , database , programming language , wireless

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research