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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Bibliographic Details
Published in:BMC bioinformatics Vol. 20; no. 1; pp. 42 - 5
Main Authors: 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.
Format: Journal Article
Language:English
Published: London BioMed Central 21.01.2019
BioMed Central Ltd
BMC
Subjects:
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
Online Access:Get full text
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Summary: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
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-019-2610-2