A Survey of Approaches and Frameworks to Carry Out Genomic Data Analysis on the Cloud

High Performance Computing (HPC) clouds have started to change the way how research in science, in particular medicine and genomics (bioinformatics) is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. However, most HPC clouds are provided at an Infrastructure as a Service (IaaS) level, users are presented with a set of virtual servers which need to be put together to form HPC environments via time consuming resource management and software configuration tasks, which make them practically unusable by discipline, non-computing specialists. In response, there is a new trend to expose cloud applications as services to simplify access and execution on clouds. This paper firstly examines commonly used cloud-based genomic analysis services (Tuxedo Suite, Galaxy and Cloud Bio Linux). As a follow up, we propose two new solutions (HPCaaS and Uncinus), which aim to automate aspects of the service development and deployment process. By comparing and contrasting these five solutions, we identify key mechanisms of service creation, execution and access that are required to support genomic research on the SaaS cloud, in particular by discipline specialists.