text: abstract—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.
  keywords—cloud computing, r programming, bioconductor,
  amazon web services, data analytics