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CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

BACKGROUND: Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access...

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Autores principales: Angiuoli, Samuel V, Matalka, Malcolm, Gussman, Aaron, Galens, Kevin, Vangala, Mahesh, Riley, David R, Arze, Cesar, White, James R, White, Owen, Fricke, W Florian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3228541/
https://www.ncbi.nlm.nih.gov/pubmed/21878105
http://dx.doi.org/10.1186/1471-2105-12-356
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author Angiuoli, Samuel V
Matalka, Malcolm
Gussman, Aaron
Galens, Kevin
Vangala, Mahesh
Riley, David R
Arze, Cesar
White, James R
White, Owen
Fricke, W Florian
author_facet Angiuoli, Samuel V
Matalka, Malcolm
Gussman, Aaron
Galens, Kevin
Vangala, Mahesh
Riley, David R
Arze, Cesar
White, James R
White, Owen
Fricke, W Florian
author_sort Angiuoli, Samuel V
collection PubMed
description BACKGROUND: Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. RESULTS: We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. CONCLUSION: The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.
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spelling pubmed-32285412011-12-07 CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing Angiuoli, Samuel V Matalka, Malcolm Gussman, Aaron Galens, Kevin Vangala, Mahesh Riley, David R Arze, Cesar White, James R White, Owen Fricke, W Florian BMC Bioinformatics Software BACKGROUND: Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. RESULTS: We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. CONCLUSION: The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. BioMed Central 2011-08-30 /pmc/articles/PMC3228541/ /pubmed/21878105 http://dx.doi.org/10.1186/1471-2105-12-356 Text en Copyright © 2011 Angiuoli et al; licensee BioMed Central Ltd. https://creativecommons.org/licenses/by/2.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Angiuoli, Samuel V
Matalka, Malcolm
Gussman, Aaron
Galens, Kevin
Vangala, Mahesh
Riley, David R
Arze, Cesar
White, James R
White, Owen
Fricke, W Florian
CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing
title CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing
title_full CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing
title_fullStr CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing
title_full_unstemmed CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing
title_short CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing
title_sort clovr: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3228541/
https://www.ncbi.nlm.nih.gov/pubmed/21878105
http://dx.doi.org/10.1186/1471-2105-12-356
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