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Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows
BACKGROUND: Bioinformaticians collaborating with life scientists need software that allows them to involve their collaborators in the process of data analysis. RESULTS: We have developed a web application that allows researchers to publish and execute data analysis scripts. Within the platform bioin...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346607/ https://www.ncbi.nlm.nih.gov/pubmed/32640986 http://dx.doi.org/10.1186/s12859-020-03602-6 |
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author | Aberra, Natay Sebastian, Aswathy Maloy, Aaron P. Rees, Christopher B. Bartron, Meredith L. Albert, Istvan |
author_facet | Aberra, Natay Sebastian, Aswathy Maloy, Aaron P. Rees, Christopher B. Bartron, Meredith L. Albert, Istvan |
author_sort | Aberra, Natay |
collection | PubMed |
description | BACKGROUND: Bioinformaticians collaborating with life scientists need software that allows them to involve their collaborators in the process of data analysis. RESULTS: We have developed a web application that allows researchers to publish and execute data analysis scripts. Within the platform bioinformaticians are able to deploy data analysis workflows (recipes) that their collaborators can execute via point and click interfaces. The results generated by the recipes are viewable via the web interface and consist of a snapshot of all the commands, printed messages and files that have been generated during the recipe run. A demonstration version of our software is available at https://www.bioinformatics.recipes/. Detailed documentation for the software is available at: https://bioinformatics-recipes.readthedocs.io. The source code for the software is distributed through GitHub at https://github.com/ialbert/biostar-central. CONCLUSIONS: Our software platform supports collaborative interactions between bioinformaticians and life scientists. The software is presented via a web application that provides a high utility and user-friendly approach for conducting reproducible research. The recipes developed and shared through the web application are generic, with broad applicability and may be downloaded and executed on other computing platforms. |
format | Online Article Text |
id | pubmed-7346607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73466072020-07-14 Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows Aberra, Natay Sebastian, Aswathy Maloy, Aaron P. Rees, Christopher B. Bartron, Meredith L. Albert, Istvan BMC Bioinformatics Software BACKGROUND: Bioinformaticians collaborating with life scientists need software that allows them to involve their collaborators in the process of data analysis. RESULTS: We have developed a web application that allows researchers to publish and execute data analysis scripts. Within the platform bioinformaticians are able to deploy data analysis workflows (recipes) that their collaborators can execute via point and click interfaces. The results generated by the recipes are viewable via the web interface and consist of a snapshot of all the commands, printed messages and files that have been generated during the recipe run. A demonstration version of our software is available at https://www.bioinformatics.recipes/. Detailed documentation for the software is available at: https://bioinformatics-recipes.readthedocs.io. The source code for the software is distributed through GitHub at https://github.com/ialbert/biostar-central. CONCLUSIONS: Our software platform supports collaborative interactions between bioinformaticians and life scientists. The software is presented via a web application that provides a high utility and user-friendly approach for conducting reproducible research. The recipes developed and shared through the web application are generic, with broad applicability and may be downloaded and executed on other computing platforms. BioMed Central 2020-07-08 /pmc/articles/PMC7346607/ /pubmed/32640986 http://dx.doi.org/10.1186/s12859-020-03602-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Aberra, Natay Sebastian, Aswathy Maloy, Aaron P. Rees, Christopher B. Bartron, Meredith L. Albert, Istvan Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
title | Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
title_full | Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
title_fullStr | Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
title_full_unstemmed | Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
title_short | Bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
title_sort | bioinformatics recipes: creating, executing and distributing reproducible data analysis workflows |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346607/ https://www.ncbi.nlm.nih.gov/pubmed/32640986 http://dx.doi.org/10.1186/s12859-020-03602-6 |
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