PT  - JOURNAL ARTICLE
AU  - Christine P’ng
AU  - Jeffrey Green
AU  - Lauren C. Chong
AU  - Daryl Waggott
AU  - Stephenie D. Prokopec
AU  - Mehrdad Shamsi
AU  - Francis Nguyen
AU  - Denise Y.F. Mak
AU  - Felix Lam
AU  - Marco A. Albuquerque
AU  - Ying Wu
AU  - Esther H. Jung
AU  - Maud H.W. Starmans
AU  - Michelle A. Chan-Seng-Yue
AU  - Cindy Q. Yao
AU  - Bianca Liang
AU  - Emilie Lalonde
AU  - Syed Haider
AU  - Nicole A. Simone
AU  - Dorota Sendorek
AU  - Kenneth C. Chu
AU  - Nathalie C. Moon
AU  - Natalie S. Fox
AU  - Michal R. Grzadkowski
AU  - Nicholas J. Harding
AU  - Clement Fung
AU  - Amanda R. Murdoch
AU  - Kathleen E. Houlahan
AU  - Jianxin Wang
AU  - David R. Garcia
AU  - Richard de Borja
AU  - Ren X. Sun
AU  - Xihui Lin
AU  - Gregory M. Chen
AU  - Aileen Lu
AU  - Yu-Jia Shiah
AU  - Amin Zia
AU  - Ryan Kearns
AU  - Paul C. Boutros
TI  - BPG: Seamless, Automated and Interactive Visualization of Scientific Data
AID  - 10.1101/156067
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 156067
4099  - http://biorxiv.org/content/early/2017/06/26/156067.short
4100  - http://biorxiv.org/content/early/2017/06/26/156067.full
AB  - We introduce BPG, an easy-to-use framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes novel methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it ideal for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for seamless integration with computational pipelines. BPG is available at http://labs.oicr.on.ca/boutros-lab/software/bpg