Title |
Scalable and cost-effective NGS genotyping in the cloud
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Published in |
BMC Medical Genomics, October 2015
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DOI | 10.1186/s12920-015-0134-9 |
Pubmed ID | |
Authors |
Yassine Souilmi, Alex K. Lancaster, Jae-Yoon Jung, Ettore Rizzo, Jared B. Hawkins, Ryan Powles, Saaïd Amzazi, Hassan Ghazal, Peter J. Tonellato, Dennis P. Wall |
Abstract |
While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars. We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 4% |
United Kingdom | 1 | 1% |
India | 1 | 1% |
Unknown | 63 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 19 | 28% |
Student > Ph. D. Student | 14 | 21% |
Student > Master | 8 | 12% |
Student > Postgraduate | 7 | 10% |
Student > Bachelor | 5 | 7% |
Other | 9 | 13% |
Unknown | 6 | 9% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 17 | 25% |
Biochemistry, Genetics and Molecular Biology | 16 | 24% |
Computer Science | 13 | 19% |
Business, Management and Accounting | 4 | 6% |
Engineering | 4 | 6% |
Other | 7 | 10% |
Unknown | 7 | 10% |