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DockerBIO: web application for efficient use of bioinformatics Docker images

BACKGROUND AND OBJECTIVE: Docker is a light containerization program that shows almost the same performance as a local environment. Recently, many bioinformatics tools have been distributed as Docker images that include complex settings such as libraries, configurations, and data if needed, as well...

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Detalles Bibliográficos
Autores principales: Kwon, ChangHyuk, Kim, Jason, Ahn, Jaegyoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266945/
https://www.ncbi.nlm.nih.gov/pubmed/30515360
http://dx.doi.org/10.7717/peerj.5954
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author Kwon, ChangHyuk
Kim, Jason
Ahn, Jaegyoon
author_facet Kwon, ChangHyuk
Kim, Jason
Ahn, Jaegyoon
author_sort Kwon, ChangHyuk
collection PubMed
description BACKGROUND AND OBJECTIVE: Docker is a light containerization program that shows almost the same performance as a local environment. Recently, many bioinformatics tools have been distributed as Docker images that include complex settings such as libraries, configurations, and data if needed, as well as the actual tools. Users can simply download and run them without making the effort to compile and configure them, and can obtain reproducible results. In spite of these advantages, several problems remain. First, there is a lack of clear standards for distribution of Docker images, and the Docker Hub often provides multiple images with the same objective but different uses. For these reasons, it can be difficult for users to learn how to select and use them. Second, Docker images are often not suitable as a component of a pipeline, because many of them include big data. Moreover, a group of users can have difficulties when sharing a pipeline composed of Docker images. Users of a group may modify scripts or use different versions of the data, which causes inconsistent results. METHODS AND RESULTS: To handle the problems described above, we developed a Java web application, DockerBIO, which provides reliable, verified, light-weight Docker images for various bioinformatics tools and for various kinds of reference data. With DockerBIO, users can easily build a pipeline with tools and data registered at DockerBIO, and if necessary, users can easily register new tools or data. Built pipelines are registered in DockerBIO, which provides an efficient running environment for the pipelines registered at DockerBIO. This enables user groups to run their pipelines without expending much effort to copy and modify them.
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spelling pubmed-62669452018-12-04 DockerBIO: web application for efficient use of bioinformatics Docker images Kwon, ChangHyuk Kim, Jason Ahn, Jaegyoon PeerJ Bioinformatics BACKGROUND AND OBJECTIVE: Docker is a light containerization program that shows almost the same performance as a local environment. Recently, many bioinformatics tools have been distributed as Docker images that include complex settings such as libraries, configurations, and data if needed, as well as the actual tools. Users can simply download and run them without making the effort to compile and configure them, and can obtain reproducible results. In spite of these advantages, several problems remain. First, there is a lack of clear standards for distribution of Docker images, and the Docker Hub often provides multiple images with the same objective but different uses. For these reasons, it can be difficult for users to learn how to select and use them. Second, Docker images are often not suitable as a component of a pipeline, because many of them include big data. Moreover, a group of users can have difficulties when sharing a pipeline composed of Docker images. Users of a group may modify scripts or use different versions of the data, which causes inconsistent results. METHODS AND RESULTS: To handle the problems described above, we developed a Java web application, DockerBIO, which provides reliable, verified, light-weight Docker images for various bioinformatics tools and for various kinds of reference data. With DockerBIO, users can easily build a pipeline with tools and data registered at DockerBIO, and if necessary, users can easily register new tools or data. Built pipelines are registered in DockerBIO, which provides an efficient running environment for the pipelines registered at DockerBIO. This enables user groups to run their pipelines without expending much effort to copy and modify them. PeerJ Inc. 2018-11-27 /pmc/articles/PMC6266945/ /pubmed/30515360 http://dx.doi.org/10.7717/peerj.5954 Text en © 2018 Kwon et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Kwon, ChangHyuk
Kim, Jason
Ahn, Jaegyoon
DockerBIO: web application for efficient use of bioinformatics Docker images
title DockerBIO: web application for efficient use of bioinformatics Docker images
title_full DockerBIO: web application for efficient use of bioinformatics Docker images
title_fullStr DockerBIO: web application for efficient use of bioinformatics Docker images
title_full_unstemmed DockerBIO: web application for efficient use of bioinformatics Docker images
title_short DockerBIO: web application for efficient use of bioinformatics Docker images
title_sort dockerbio: web application for efficient use of bioinformatics docker images
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266945/
https://www.ncbi.nlm.nih.gov/pubmed/30515360
http://dx.doi.org/10.7717/peerj.5954
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