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Bringing numerous methods for expression and promoter analysis to a public cloud computing service
SUMMARY: Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030968/ https://www.ncbi.nlm.nih.gov/pubmed/29126246 http://dx.doi.org/10.1093/bioinformatics/btx692 |
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author | Polański, Krzysztof Gao, Bo Mason, Sam A Brown, Paul Ott, Sascha Denby, Katherine J Wild, David L |
author_facet | Polański, Krzysztof Gao, Bo Mason, Sam A Brown, Paul Ott, Sascha Denby, Katherine J Wild, David L |
author_sort | Polański, Krzysztof |
collection | PubMed |
description | SUMMARY: Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project. AVAILABILITY AND IMPLEMENTATION: The integrated apps can be found at http://www.cyverse.org/discovery-environment, while the raw code is available at https://github.com/cyversewarwick and the corresponding Docker images are housed at https://hub.docker.com/r/cyversewarwick/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6030968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60309682018-07-10 Bringing numerous methods for expression and promoter analysis to a public cloud computing service Polański, Krzysztof Gao, Bo Mason, Sam A Brown, Paul Ott, Sascha Denby, Katherine J Wild, David L Bioinformatics Applications Notes SUMMARY: Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project. AVAILABILITY AND IMPLEMENTATION: The integrated apps can be found at http://www.cyverse.org/discovery-environment, while the raw code is available at https://github.com/cyversewarwick and the corresponding Docker images are housed at https://hub.docker.com/r/cyversewarwick/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-03-01 2017-11-06 /pmc/articles/PMC6030968/ /pubmed/29126246 http://dx.doi.org/10.1093/bioinformatics/btx692 Text en © The Author 2017. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Polański, Krzysztof Gao, Bo Mason, Sam A Brown, Paul Ott, Sascha Denby, Katherine J Wild, David L Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
title | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
title_full | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
title_fullStr | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
title_full_unstemmed | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
title_short | Bringing numerous methods for expression and promoter analysis to a public cloud computing service |
title_sort | bringing numerous methods for expression and promoter analysis to a public cloud computing service |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030968/ https://www.ncbi.nlm.nih.gov/pubmed/29126246 http://dx.doi.org/10.1093/bioinformatics/btx692 |
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