Archive Number: 4.424
Status of Thesis: Open
With the advent of next generation DNA sequencing and availability of large volumes of genomic data, storage and processing of genomic data have become a bottleneck in genomic research. Cloud computing has been proposed as a viable solution to overcome the deficits in storage and processing resources. Hence, increasing numbers of researchers in the field of genomics are turning to the cloud. Various platforms that allow for performing analyses of genomic data in cloud computing environments are available today (i.e., Galaxy Cloud, CloudDOE, and DNAnexus). Yet, little (structured) knowledge exists about these services’ characteristics, similarities, and differences. Such an overview would enable researchers to select the platform that is best suited for their research endeavor and also help to uncover research potentials on genomic cloud services in general.
The objective of this thesis is to evaluate and further develop a taxonomy of cloud computing platforms in genomics.
Stein, L. D. (2010). "The case for cloud computing in genome informatics." Genome Biology (11:5), pp. 207-213.
Chung, W.-C., Chen, C.-C., Ho, J.-M., Lin, C.-Y., Hsu, W.-L., Wang, Y.-C., Lee, D. T., Lai, F., Huang, C.-W. and Chang, Y.-J. (2014). "CloudDOE: A User-Friendly Tool for Deploying Hadoop Clouds and Analyzing High-Throughput Sequencing Data with MapReduce." PLoS ONE (9:6), p. e98146.
Methods: Nickerson, R.C., Varshney, U., Muntermann, J. (2013): "A method for taxonomy development and its application in information systems". European Journal of Information Systems (2013:22), pp. 336–359.
Webster, J. and Watson, R. T. 2002. "Analyzing the Past to Prepare for the Future: Writing a Literature Review," MIS Quarterly (26:2), pp. xiii-xxiii.
Exemplary list of genomic cloud services: