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
Link To Document