RBioCloud: A Light-weight Framework for Bioconductor and R-based Jobs on the Cloud
This work addresses a domain-specific problem for biologists and bioinformaticists by providing a tool to simplify cloud-based genomic data analysis, though it is incremental as it builds on existing cloud and R/Bioconductor technologies.
The paper tackles the challenge of executing R-based Bioconductor jobs on cloud infrastructure without requiring extensive cloud expertise, by developing RBioCloud, a light-weight framework with command-line tools for resource and data management, validated through three biological test cases.
Large-scale ad hoc analytics of genomic data is popular using the R-programming language supported by 671 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their scalability and their low maintenance cost, all of which are offered by the cloud. While Biologists and Bioinformaticists can take an analytical job and execute it on their personal workstations, it remains challenging to seamlessly execute the job on the cloud infrastructure without extensive knowledge of the cloud dashboard. How analytical jobs can not only with minimum effort be executed on the cloud, but also how both the resources and data required by the job can be managed is explored in this paper. An open-source light-weight framework for executing R-scripts using Bioconductor packages, referred to as `RBioCloud', is designed and developed. RBioCloud offers a set of simple command-line tools for managing the cloud resources, the data and the execution of the job. Three biological test cases validate the feasibility of RBioCloud. The framework is publicly available from http://www.rbiocloud.com.