Abstract
Cloud computing provides a promising solution to the big data problem associated with next generation sequencing applications. The increasing number of cloud service providers, who compete in terms of performance and price, is a clear indication of a growing market with high demand. However, current cloud computing based applications in bioinformatics do not profit from this progress, because they are still limited to just one cloud service provider. In this paper, we present different use case scenarios using hybrid services and resources from multiple cloud providers for bioinformatics applications. We also present a new version of the elasticHPC package to realize these scenarios and to support the creation of cloud computing resources over multiple cloud platforms, including Amazon, Google, Azure, and clouds supporting OpenStack. The instances created on these cloud environments are pre-configured to run big sequence analysis tasks using a large set of pre-installed software tools and parallelization techniques. In addition to its flexibility, we show by experiments that the use of hybrid cloud resources from different providers can save time and cost.