Pineplot

Abstract

An effective publication-quality visualization tells a concise story from data. Methods and tools that facilitate making such visualizations are valuable to the scientific community. In this paper, we introduce pineplot, an R package for generating insightful visualizations called pine plots. Pine plots are applicable to a wide variety of datasets and create a holistic picture of the relationship between variables across different experimental conditions. A pine plot provides a means to visualize a group of symmetric matrices, each represented by triangular heat maps. Pine plots can be used to visualize large datasets for exploratory data analysis while controlling for different potentially confounding factors. The utility of the package is demonstrated by visualizing gene expression values of tissue-specific genes from RNA-seq data and the clinical factors in a liver disease and a heart disease dataset. The implementation of pineplot offers a straightforward procedure for generating pine plots; full control of the aesthetic elements of generated plots; and the possibility of augmenting generated plots with extra layers of graphical elements to further extend their usability.