Using Cloud Computing for Comparative Genomics
Author Information
Author(s): Wall Dennis P, Kudtarkar Parul, Fusaro Vincent A, Pivovarov Rimma, Patil Prasad, Tonellato Peter J
Primary Institution: Harvard Medical School
Hypothesis
Can cloud computing environments alleviate the computational demands of comparative genomics?
Conclusion
Cloud computing significantly enhances the speed and flexibility of comparative genomics algorithms while maintaining manageable costs.
Supporting Evidence
- Over 300,000 RSD-cloud processes were run within the EC2.
- The total computation time was just under 70 hours at a cost of $6,302.
- The study involved 454 fully sequenced genomes, including 55 new genomes.
Takeaway
This study shows that using cloud computing can help scientists analyze many genomes quickly and cheaply, making it easier to study how different species are related.
Methodology
The reciprocal smallest distance algorithm was adapted to run on Amazon's Elastic Compute Cloud, processing over 300,000 jobs across 454 genomes.
Limitations
The study primarily focused on the RSD algorithm and may not generalize to all comparative genomics tools.
Digital Object Identifier (DOI)
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