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BPG: Seamless, automated and interactive visualization of scientific data.

  • Author(s): P'ng, Christine;
  • Green, Jeffrey;
  • Chong, Lauren C;
  • Waggott, Daryl;
  • Prokopec, Stephenie D;
  • Shamsi, Mehrdad;
  • Nguyen, Francis;
  • Mak, Denise YF;
  • Lam, Felix;
  • Albuquerque, Marco A;
  • Wu, Ying;
  • Jung, Esther H;
  • Starmans, Maud HW;
  • 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
  • et al.
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.

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