Streaming Support for Data Intensive Cloud-Based Sequence Analysis

Issa, Shadi A.; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J.; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed (2013). Streaming Support for Data Intensive Cloud-Based Sequence Analysis. BioMed research international, 2013(8), pp. 1-16. Hindawi Publishing Corporation 10.1155/2013/791051

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Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client’s site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

Item Type:

Journal Article (Original Article)

UniBE Contributor:

Bruggmann, Rémy

Subjects:

500 Science > 570 Life sciences; biology

ISSN:

2314-6133

Publisher:

Hindawi Publishing Corporation

Language:

English

Submitter:

Rémy Bruggmann

Date Deposited:

09 Jul 2014 15:08

Last Modified:

08 Dec 2014 19:37

Publisher DOI:

10.1155/2013/791051

BORIS DOI:

10.7892/boris.47842

URI:

https://boris.unibe.ch/id/eprint/47842

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