Abstract
BackgroundWidespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is “cloud computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate “as is” use by experimental biologists.ResultsWe present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs.ConclusionsThe expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.
Highlights
Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research
Galaxy CloudMan is ideal for independent researchers and small labs that have a specific or periodic need for computational resources but lack informatics expertise and commitment to manage and maintain a computational cluster
The process of instantiating a CloudMan compute cluster consists of three steps: (1) create an Amazon Web Services (AWS) account and sign up for the EC2 and S3 services, (2) use the AWS Management Console to start a master EC2 instance, and (3) use the CloudMan web console on the master instance to manage the cluster size
Summary
Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. A computational model – cloud computing [1] – has recently emerged and is ideally suited for the analysis of large-scale sequence data In this model, computation and storage exist as virtual resources in remote datacenters, and can be dynamically allocated and released as needed. Cloud resources are acquired as independent, stripped-down units that must first be customized for the intended use They must be configured to work in unison and a mechanism must be provided for the data uploaded and analyzed on those resources to persist beyond the life of a (usually transient) cloud compute resource
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