A gene is a sequence of DNA bases through which genetic information is passed on to the next generation. Most genes encode for proteins that ultimately control cellular function. Understanding the interrelation between genes without the application of statistical methods can be a daunting task. Correlation analysis is a powerful approach to determine the strength of association between two variables (e.g., gene-wise expression). Moreover, it becomes essential to visualize this data to establish patterns and derive insight. The most common method for gene expression visualization is to use correlation heatmaps in which the colors of the plot represent strength of co-expression. In order to address this requirement, we developed a visualization tool called BioCPR: Biological Correlation Plots in R. This tool performs both correlation analysis and subsequent visualization in the form of an interactive heatmap, improving both usability and interpretation of the data. BioCPR is an R Shiny-based application and can be run locally in Rstudio or a web browser.