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An Open-source Azure Solution for Scalable Genomics Workflows

Abstract:
We present an open-source Azure solution for running scalable genomics workflows. It benefits from state-of-art distributed workflow framework, container and cloud technologies and allows users to create a cluster that is scaled to suit their workload in minutes. We describe the design decisions, solution testing and automation options to support a variety of users for their genomic data analytics. The solution demonstrates a generic and customizable approach to run genomic data analytics workflows on a cloud environment.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/SERVICES.2018.00033

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
ORCID:
0000-0002-2265-2275
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
ORCID:
0000-0002-9129-3149
Publisher:
IEEE Publisher's website
Host title:
2018 IEEE World Congress on Services (SERVICES)
Pages:
39-40
Publication date:
2018-05-01
Acceptance date:
2018-01-04
Event title:
2018 IEEE World Congress on Services (SERVICES)
Event location:
San Francisco, CA, USA
Event website:
https://conferences.computer.org/services/2018/
Event start date:
2018-07-02
Event end date:
2018-07-07
DOI:
ISSN:
2378-3818
ISBN:
9781538673744
Language:
English
Keywords:
Pubs id:
951182
Local pid:
pubs:951182
Deposit date:
2020-06-15

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