As the cost of next generation sequencing decreases and the accessibility increases many labs will be in a position to perform NGS experiments, at one point limited to the mega-lab. With NGS data comes the necessity for adequate analysis capabilities to make sense of millions to billions of short sequence reads. These large data sets require high performance computing power for their analysis, generally not found in office computers that service the standard science lab. The Galaxy Project has developed an instance of its powerful and user friendly environment to be used with Amazon Web Services to allow researchers to perform NGS analysis on the cloud. This is a very convenient option for researchers who are in need of high computational power for a limited number of experiments (time) and may not have access to the necessary computational infrastructure. Here we discuss our experiences as cellular and molecular biologists with no computational/programming background performing RNA-seq analysis using the Galaxy CloudMan. We aim to create resource that can help the non-computational biologist establish cloud space and perform analyses with minimal programming/coding, to maximize the efficiency of the biologist and to allow her/him to focus on the biology of the experiment. This work will hopefully contribute to the dialogue between biologists and developers to maximize the efficiency of both parties.
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