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Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

delete2014-06-01
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OA
AI
刘波 (Bo Liu) *
R
Ravi Madduri
B
Borja Sotomayor
K
Kyle Chard
Ł
Łukasz Łaciński
U
Utpal Dave
李建强 cover
李建强 (Jianqiang Li)
刘春晨 (Chunchen Liu)
I
Ian Foster
DOI:10.1016/j.jbi.2014.01.005delete
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Abstract

Abstract

En 中文
Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. (C) 2014 Elsevier Inc. All rights reserved.
Keywords:
Bioinformatics
Scientific workflow
Sequencing analyses
Cloud computing
Galaxy
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Journal of Biomedical Informatics cover
Journal of Biomedical Informatics
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U
university of chicago
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united states department of energy (doe)
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Beijing University of Technology
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