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A bedr way of genomic interval processing
BACKGROUND: Next-generation sequencing is making it critical to robustly and rapidly handle genomic ranges within standard pipelines. Standard use-cases include annotating sequence ranges with gene or other genomic annotation, merging multiple experiments together and subsequently quantifying and vi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5157088/ https://www.ncbi.nlm.nih.gov/pubmed/27999613 http://dx.doi.org/10.1186/s13029-016-0059-5 |
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author | Haider, Syed Waggott, Daryl Lalonde, Emilie Fung, Clement Liu, Fei-Fei Boutros, Paul C. |
author_facet | Haider, Syed Waggott, Daryl Lalonde, Emilie Fung, Clement Liu, Fei-Fei Boutros, Paul C. |
author_sort | Haider, Syed |
collection | PubMed |
description | BACKGROUND: Next-generation sequencing is making it critical to robustly and rapidly handle genomic ranges within standard pipelines. Standard use-cases include annotating sequence ranges with gene or other genomic annotation, merging multiple experiments together and subsequently quantifying and visualizing the overlap. The most widely-used tools for these tasks work at the command-line (e.g. BEDTools) and the small number of available R packages are either slow or have distinct semantics and features from command-line interfaces. RESULTS: To provide a robust R-based interface to standard command-line tools for genomic coordinate manipulation, we created bedr. This open-source R package can use either BEDTools or BEDOPS as a back-end and performs data-manipulation extremely quickly, creating R data structures that can be readily interfaced with existing computational pipelines. It includes data-visualization capabilities and a number of data-access functions that interface with standard databases like UCSC and COSMIC. CONCLUSIONS: bedr package provides an open source solution to enable genomic interval data manipulation and restructuring in R programming language which is commonly used in bioinformatics, and therefore would be useful to bioinformaticians and genomic researchers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13029-016-0059-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5157088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-51570882016-12-20 A bedr way of genomic interval processing Haider, Syed Waggott, Daryl Lalonde, Emilie Fung, Clement Liu, Fei-Fei Boutros, Paul C. Source Code Biol Med Software BACKGROUND: Next-generation sequencing is making it critical to robustly and rapidly handle genomic ranges within standard pipelines. Standard use-cases include annotating sequence ranges with gene or other genomic annotation, merging multiple experiments together and subsequently quantifying and visualizing the overlap. The most widely-used tools for these tasks work at the command-line (e.g. BEDTools) and the small number of available R packages are either slow or have distinct semantics and features from command-line interfaces. RESULTS: To provide a robust R-based interface to standard command-line tools for genomic coordinate manipulation, we created bedr. This open-source R package can use either BEDTools or BEDOPS as a back-end and performs data-manipulation extremely quickly, creating R data structures that can be readily interfaced with existing computational pipelines. It includes data-visualization capabilities and a number of data-access functions that interface with standard databases like UCSC and COSMIC. CONCLUSIONS: bedr package provides an open source solution to enable genomic interval data manipulation and restructuring in R programming language which is commonly used in bioinformatics, and therefore would be useful to bioinformaticians and genomic researchers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13029-016-0059-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-12-15 /pmc/articles/PMC5157088/ /pubmed/27999613 http://dx.doi.org/10.1186/s13029-016-0059-5 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Software Haider, Syed Waggott, Daryl Lalonde, Emilie Fung, Clement Liu, Fei-Fei Boutros, Paul C. A bedr way of genomic interval processing |
title | A bedr way of genomic interval processing |
title_full | A bedr way of genomic interval processing |
title_fullStr | A bedr way of genomic interval processing |
title_full_unstemmed | A bedr way of genomic interval processing |
title_short | A bedr way of genomic interval processing |
title_sort | bedr way of genomic interval processing |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5157088/ https://www.ncbi.nlm.nih.gov/pubmed/27999613 http://dx.doi.org/10.1186/s13029-016-0059-5 |
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