Interactive data visualization is imperative in the biological sciences. The 
development of independent layers of interactivity has been in pursuit in the 
visualization community. We developed bigPint, a data visualization package 
available on Bioconductor under the GPL-3 license 
(https://bioconductor.org/packages/release/bioc/html/bigPint.html). Our software 
introduces new visualization technology that enables independent layers of 
interactivity using Plotly in R, which aids in the exploration of large 
biological datasets. The bigPint package presents modernized versions of 
scatterplot matrices, volcano plots, and litre plots through the implementation 
of layered interactivity. These graphics have detected normalization issues, 
differential expression designation problems, and common analysis errors in 
public RNA-sequencing datasets. Researchers can apply bigPint graphics to their 
data by following recommended pipelines written in reproducible code in the user 
manual. In this paper, we explain how we achieved the independent layers of 
interactivity that are behind bigPint graphics. Pseudocode and source code are 
provided. Computational scientists can leverage our open-source code to expand 
upon our layered interactive technology and/or apply it in new ways toward other 
computational biology tasks.