Diceplot: A package for high dimensional categorical data visualization

TL;DR

Diceplot is an R package that provides innovative visualizations for high-dimensional categorical data, enabling intuitive analysis of complex biological datasets such as pathway dysregulation across conditions.

Contribution

The paper introduces Dice plots and domino plots as new visualization methods for multidimensional categorical data, implemented in an accessible R package.

Findings

Effective visualization of up to four categorical variables.

Facilitates pathway analysis and biological data interpretation.

Available as open-source software.

Abstract

Visualization of multidimensional, categorical data is a common challenge across scientific areas and, in particular, the life sciences. The goal is to create a comprehensive overview of the underlying data which allows to assess multiple variables intuitively. One application where such visualizations are particularly useful is pathway analysis, where we check for dysregulation in known biological regulatory mechanisms and functions across multiple conditions. Here, we propose a new visualization approach that codes such data in a comprehensive and intuitive representation: Dice plots visualize up to four distinct categorical classes in a single view that consist of multiple elements resembling the faces of dice, whereas domino plots add an additional layer of information for binary comparison. The code is available as the diceplot R package, as pydiceplot on pip and at https://github.com/maflot.