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BPG: Seamless, automated and interactive visualization of scientific data
Christine P'ng1, Jeffrey Green1, Lauren C Chong1
1Ontario Institute for Cancer Research, Toronto, Canada.
BMC Bioinformatics
|January 23, 2019
Summary
We introduce BPG, a framework for generating publication-quality, highly-customizable plots in R. This open-source package aids in visualizing complex datasets and integrating interactive tools with computational pipelines.
Area of Science:
- Data Visualization
- Bioinformatics
- Statistical Computing
Background:
- The R statistical environment is widely used for data analysis.
- Generating publication-quality, customizable plots is crucial for scientific communication.
- Existing tools may lack flexibility for complex, high-dimensional datasets.
Purpose of the Study:
- Introduce BPG (BoutrosLab.plotting.general), a novel framework for data visualization in R.
- Provide a tool that generates publication-quality, highly-customizable plots.
- Facilitate the integration of interactive and scripted data visualization.
Main Methods:
- Developed an open-source R package, BPG.
- Incorporated multiple methods for displaying high-dimensional data.
- Integrated a web-based interactive tool for online figure customization.
Main Results:
- BPG facilitates the generation of complex multi-panel figures suitable for intricate datasets.
- The package offers a user-friendly interface for customizing plots.
- R code generated from the interactive tool can be downloaded for seamless integration into computational workflows.
Conclusions:
- BPG offers a new approach to link interactive and scripted data visualization.
- The framework enhances the creation of publication-quality plots from complex datasets.
- BPG is available as an open-source package via CRAN and a dedicated website.
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