title: Cloud computing for comparative genomics.
abstract: BACKGROUND
  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, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes.
  
  
  RESULTS
  We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD.
  
  
  CONCLUSIONS
  The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems.
authors.affiliation: Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA. dpwall@hms.harvard.edu
authors.forename: Dennis P
authors.initials: DP
authors.lastname: Wall
authors.forename: Parul
authors.initials: P
authors.lastname: Kudtarkar
authors.forename: Vincent A
authors.initials: VA
authors.lastname: Fusaro
authors.forename: Rimma
authors.initials: R
authors.lastname: Pivovarov
authors.forename: Prasad
authors.initials: P
authors.lastname: Patil
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Tonellato
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D016678:Genome; D023281:Genomics / Q000379:methods*