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Large-scale ad hoc analytics of genomic data is popular using theR-programming language supported by 671 software packages provided byBioconductor. More recently, analytical jobs are benefitting from on-demandcomputing and storage, their scalability and their low maintenance cost, all ofwhich are offered by the cloud. While Biologists and Bioinformaticists can takean analytical job and execute it on their personal workstations, it remainschallenging to seamlessly execute the job on the cloud infrastructure withoutextensive knowledge of the cloud dashboard. How analytical jobs can not onlywith minimum effort be executed on the cloud, but also how both the resourcesand data required by the job can be managed is explored in this paper. Anopen-source light-weight framework for executing R-scripts using Bioconductorpackages, referred to as `RBioCloud', is designed and developed. RBioCloudoffers a set of simple command-line tools for managing the cloud resources, thedata and the execution of the job. Three biological test cases validate thefeasibility of RBioCloud. The framework is publicly available fromhttp://www.rbiocloud.com.

RBioCloud: A Light-weight Framework for Bioconductor and R-based Jobs on the Cloud