학술논문
BPG: Seamless, automated and interactive visualization of scientific data.
Document Type
article
Author
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
Source
BMC bioinformatics. 20(1)
Subject
Language
Abstract
BackgroundWe introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment.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.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.