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

Blesson Varghese; Ishan Patel; Adam David Barker

doi:10.1109/TCBB.2014.2361327

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

Blesson Varghese, Ishan Patel, Adam David Barker

School of Computer Science

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	871-878
Number of pages	9
Journal	IEEE/ACM Transactions on Computational Biology And Bioinformatics
Volume	12
Issue number	4
DOIs	https://doi.org/10.1109/TCBB.2014.2361327
Publication status	Published - 2 Oct 2014

Keywords

Cloud computing
R programming
Bioconductor
Amazon Web Services
Data analytics

Access to Document

10.1109/TCBB.2014.2361327

RBioCloud: A Light-weight Framework for Bioconductor and R-based Jobs on the Cloud
© 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
Accepted author manuscript, 3.51 MB

Cite this

@article{3a6614ad8d4241168ae0b859a07c6262,

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

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 {\textquoteleft}RBioCloud{\textquoteright}, 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.",

keywords = "Cloud computing, R programming, Bioconductor, Amazon Web Services, Data analytics",

author = "Blesson Varghese and Ishan Patel and Barker, {Adam David}",

year = "2014",

month = oct,

day = "2",

doi = "10.1109/TCBB.2014.2361327",

language = "English",

volume = "12",

pages = "871--878",

journal = "IEEE/ACM Transactions on Computational Biology And Bioinformatics",

issn = "1545-5963",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - RBioCloud

T2 - a light-weight framework for bioconductor and R-based jobs on the Cloud

AU - Varghese, Blesson

AU - Patel, Ishan

AU - Barker, Adam David

PY - 2014/10/2

Y1 - 2014/10/2

N2 - 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.

AB - 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.

KW - Cloud computing

KW - R programming

KW - Bioconductor

KW - Amazon Web Services

KW - Data analytics

U2 - 10.1109/TCBB.2014.2361327

DO - 10.1109/TCBB.2014.2361327

M3 - Article

SN - 1545-5963

VL - 12

SP - 871

EP - 878

JO - IEEE/ACM Transactions on Computational Biology And Bioinformatics

JF - IEEE/ACM Transactions on Computational Biology And Bioinformatics

IS - 4

ER -

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

Abstract

Keywords

Access to Document

Fingerprint

Cite this