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atSNPInfrastructure, a case study for searching billions of records while providing significant cost savings over
Christopher Harrison1,2, Sündüz Keleş1, Rebecca Hudson1
1Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, Wisconsin USA.
Abstract:
We explore the feasibility of a database storage engine housing up to 307 billion genetic Single Nucleotide Polymorphisms (SNP) for online access. We evaluate database storage engines and implement a solution utilizing factors such as dataset size, information gain, cost and hardware constraints. Our solution provides a full feature functional model for scalable storage and query-ability for researchers exploring the SNP's in the human genome. We address the scalability problem by building physical infrastructure and comparing final costs to a major cloud provider.
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