Cloud Computing for Comparative Genomics
Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, the authors redesigned a typical comparative genomics algorithm, the Reciprocal Smallest Distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). The authors then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes.