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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.

Keywords:

Data-visualization Interactive plotting Software Web-resources

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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.