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RBioCloud : a light-weight framework for bioconductor and R-based jobs on the Cloud

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06915694.pdf (3.511Mb)
Date
02/10/2014
Author
Varghese, Blesson
Patel, Ishan
Barker, Adam David
Keywords
Cloud computing
R programming
Bioconductor
Amazon Web Services
Data analytics
QA75 Electronic computers. Computer science
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Abstract
Large-scale ad hoc analytics of genomic data is popular using the R-programming language supported by over 700 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their scalability and their low maintenance cost, all of which are offered by the cloud. While Biologists and Bioinformaticists can take an analytical job and execute it on their personal workstations, it remains challenging to seamlessly execute the job on the cloud infrastructure without extensive knowledge of the cloud dashboard. How analytical jobs can not only with minimum effort be executed on the cloud, but also how both the resources and data required by the job can be managed is explored in this paper. An open-source light-weight framework for executing R-scripts using Bioconductor packages, referred to as ‘RBioCloud’, is designed and developed. RBioCloud offers a set of simple command-line tools for managing the cloud resources, the data and the execution of the job. Three biological test cases validate the feasibility of RBioCloud. The framework is available from http://www.rbiocloud.com.
Citation
Varghese , B , Patel , I & Barker , A D 2014 , ' RBioCloud : a light-weight framework for bioconductor and R-based jobs on the Cloud ' , IEEE/ACM Transactions on Computational Biology And Bioinformatics , vol. 12 , no. 4 , pp. 871-878 . https://doi.org/10.1109/TCBB.2014.2361327
Publication
IEEE/ACM Transactions on Computational Biology And Bioinformatics
Status
Peer reviewed
DOI
https://doi.org/10.1109/TCBB.2014.2361327
ISSN
1545-5963
Type
Journal article
Rights
© 2014. IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Collections
  • Computer Science Research
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/6061

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