• DocumentCode
    3078695
  • Title

    Analysing Cancer Genomics in the Elastic Cloud

  • Author

    Smowton, Christopher ; Miller, Crispin ; Wei Xing ; Balla, Andoena ; Antoniades, Demetris ; Pallis, George ; Dikaiakos, Marios D.

  • fYear
    2015
  • fDate
    4-7 May 2015
  • Firstpage
    835
  • Lastpage
    844
  • Abstract
    With the rapidly growing demand for DNA analysis, the need for storing and processing large-scale genome data has presented significant challenges. This paper describes how the Genome Analysis Toolkit (GATK) can be deployed to an elastic cloud, and defines policy to drive elastic scaling of the application. We extensively analyse the GATK to expose opportunities for resource elasticity, demonstrate that it can be practically deployed at scale in a cloud environment, and demonstrate that applying elastic scaling improves the performance to cost tradeoff achieved in a simulated environment.
  • Keywords
    DNA; biology computing; cancer; cloud computing; genomics; large-scale systems; DNA analysis; GATK; cancer genomics; elastic cloud; genome analysis toolkit; large-scale genome data; resource elasticity; Bioinformatics; Cloud computing; Elasticity; Genomics; Parallel processing; Pipelines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/CCGrid.2015.176
  • Filename
    7152567