BPG: Seamless, automated and interactive visualization of scientific data

Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, makin...

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Vydáno v:BMC bioinformatics Ročník 20; číslo 1; s. 42 - 5
Hlavní autoři: P’ng, Christine, Green, Jeffrey, Chong, Lauren C., Waggott, Daryl, Prokopec, Stephenie D., Shamsi, Mehrdad, Nguyen, Francis, Mak, Denise Y. F., Lam, Felix, Albuquerque, Marco A., Wu, Ying, Jung, Esther H., Starmans, Maud H. W., Chan-Seng-Yue, Michelle A., Yao, Cindy Q., Liang, Bianca, Lalonde, Emilie, Haider, Syed, Simone, Nicole A., Sendorek, Dorota, Chu, Kenneth C., Moon, Nathalie C., Fox, Natalie S., Grzadkowski, Michal R., Harding, Nicholas J., Fung, Clement, Murdoch, Amanda R., Houlahan, Kathleen E., Wang, Jianxin, Garcia, David R., de Borja, Richard, Sun, Ren X., Lin, Xihui, Chen, Gregory M., Lu, Aileen, Shiah, Yu-Jia, Zia, Amin, Kearns, Ryan, Boutros, Paul C.
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 21.01.2019
BioMed Central Ltd
BMC
Témata:
Algorithms
Bioinformatics
Biomedical and Life Sciences
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Data Analysis
Data processing
Data-visualization
Humans
image analysis and data visualization
Imaging
Information visualization
Interactive plotting
Life Sciences
Methods
Microarrays
R (Programming language)
Simulation Training - methods
Software
Statistical software
Visualization (Computer)
Web-resources
Canada
Interactive plotting
Software
Web-resources
Data-visualization
ISSN:1471-2105, 1471-2105
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Abstract Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. Conclusion BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general
AbstractList Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. Conclusion BPG provides a new approach for linking interactive and scripted data visualization and is available at Keywords: Data-visualization, Interactive plotting, Software, Web-resources
Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. Conclusion BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment.BACKGROUNDWe introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment.This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines.RESULTSThis open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines.BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.CONCLUSIONBPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general
Abstract Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. Conclusion BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general
ArticleNumber 42
Audience Academic
Author Mak, Denise Y. F.
Yao, Cindy Q.
Boutros, Paul C.
Lalonde, Emilie
Garcia, David R.
Zia, Amin
Chen, Gregory M.
Wang, Jianxin
Liang, Bianca
Lin, Xihui
Nguyen, Francis
Moon, Nathalie C.
Chu, Kenneth C.
Wu, Ying
Lam, Felix
Green, Jeffrey
Sendorek, Dorota
Houlahan, Kathleen E.
Chan-Seng-Yue, Michelle A.
Shamsi, Mehrdad
Harding, Nicholas J.
de Borja, Richard
Jung, Esther H.
Haider, Syed
Simone, Nicole A.
Starmans, Maud H. W.
Waggott, Daryl
Fung, Clement
Murdoch, Amanda R.
Sun, Ren X.
Lu, Aileen
Shiah, Yu-Jia
Kearns, Ryan
Albuquerque, Marco A.
Grzadkowski, Michal R.
Prokopec, Stephenie D.
Chong, Lauren C.
Fox, Natalie S.
P’ng, Christine
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  organization: Ontario Institute for Cancer Research, Department of Medical Biophysics, University of Toronto, Department of Pharmacology and Toxicology, University of Toronto, Department of Human Genetics, University of California, Department of Urology, University of California, Institute for Precision Health, University of California, Jonsson Comprehensive Cancer Center, University of California
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30665349$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords Interactive plotting
Software
Web-resources
Data-visualization
Language English
License 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.
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PublicationTitle BMC bioinformatics
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Snippet Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This...
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes...
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes...
Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This...
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment.BACKGROUNDWe introduce BPG, a...
Abstract Background We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. Results This...
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SubjectTerms Algorithms
Bioinformatics
Biomedical and Life Sciences
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Data Analysis
Data processing
Data-visualization
Humans
image analysis and data visualization
Imaging
Information visualization
Interactive plotting
Life Sciences
Methods
Microarrays
R (Programming language)
Simulation Training - methods
Software
Statistical software
Visualization (Computer)
Web-resources
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