École normale supérieure, Institut de Biologie de l'ENS, INSERM U1024, Paris, France.
Bioinformatics. 2012 Jun 1;28(11):1542-3. doi: 10.1093/bioinformatics/bts165. Epub 2012 Apr 5.
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.
Eoulsan is implemented in Java, supported on Linux systems and distributed under the LGPL License at: http://transcriptome.ens.fr/eoulsan/
我们开发了一个名为 Eoulsan 的模块化和可扩展框架，该框架基于 Hadoop 实现的 MapReduce 算法，专门用于高通量测序数据分析。Eoulsan 允许用户轻松设置云计算集群，并使用各种可用的软件解决方案自动分析多个样本。我们在亚马逊网络服务（Amazon Web Services）上的测试表明，计算成本与预订的实例数量呈线性关系，运行时间随着数据量的增加而增加。
Eoulsan 是用 Java 编写的，支持 Linux 系统，并在以下网址以 LGPL 许可证分发：http://transcriptome.ens.fr/eoulsan/
