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Use of application containers and workflows for genomic data analysis
BACKGROUND: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibili...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5248400/ https://www.ncbi.nlm.nih.gov/pubmed/28163975 http://dx.doi.org/10.4103/2153-3539.197197 |
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author | Schulz, Wade L. Durant, Thomas J. S. Siddon, Alexa J. Torres, Richard |
author_facet | Schulz, Wade L. Durant, Thomas J. S. Siddon, Alexa J. Torres, Richard |
author_sort | Schulz, Wade L. |
collection | PubMed |
description | BACKGROUND: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments. METHODS: Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing. RESULTS: While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS) data. CONCLUSIONS: With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia. |
format | Online Article Text |
id | pubmed-5248400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-52484002017-02-03 Use of application containers and workflows for genomic data analysis Schulz, Wade L. Durant, Thomas J. S. Siddon, Alexa J. Torres, Richard J Pathol Inform Technical Note BACKGROUND: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments. METHODS: Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing. RESULTS: While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS) data. CONCLUSIONS: With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia. Medknow Publications & Media Pvt Ltd 2016-12-30 /pmc/articles/PMC5248400/ /pubmed/28163975 http://dx.doi.org/10.4103/2153-3539.197197 Text en Copyright: © 2016 Journal of Pathology Informatics http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | Technical Note Schulz, Wade L. Durant, Thomas J. S. Siddon, Alexa J. Torres, Richard Use of application containers and workflows for genomic data analysis |
title | Use of application containers and workflows for genomic data analysis |
title_full | Use of application containers and workflows for genomic data analysis |
title_fullStr | Use of application containers and workflows for genomic data analysis |
title_full_unstemmed | Use of application containers and workflows for genomic data analysis |
title_short | Use of application containers and workflows for genomic data analysis |
title_sort | use of application containers and workflows for genomic data analysis |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5248400/ https://www.ncbi.nlm.nih.gov/pubmed/28163975 http://dx.doi.org/10.4103/2153-3539.197197 |
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