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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...

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Autores principales: Haider, Syed, Waggott, Daryl, Lalonde, Emilie, Fung, Clement, Liu, Fei-Fei, Boutros, Paul C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
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.
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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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