Translational bioinformatics in the cloud: an affordable alternative

被引:55
作者
Dudley, Joel T. [1 ,2 ,3 ]
Pouliot, Yannick [2 ,3 ]
Chen, Rong [2 ,3 ]
Morgan, Alexander A. [1 ,2 ,3 ]
Butte, Atul J. [2 ,3 ]
机构
[1] Stanford Univ, Sch Med, Program Biomed Informat, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Pediat, Sch Med, Stanford, CA 94305 USA
[3] Lucile Packard Childrens Hosp, Palo Alto, CA 94304 USA
来源
GENOME MEDICINE | 2010年 / 2卷
关键词
Cloud Computing; Local Cluster; Server Instance; Genomic Medicine; eQTL Analysis;
D O I
10.1186/gm172
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine.
引用
收藏
页数:6
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