Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.

Creates bar plots with rounded corners using 'ggplot2'.
    The code in this package was adapted from a solution provided by 
    Stack Overflow user 'sthoch' in the following post
    <https://stackoverflow.com/questions/62176038/r-ggplot2-bar-chart-with-round-corners-on-top-of-bar>.

Calculates additive and dominance genetic relationship matrices and their inverses, in matrix and tabular-sparse formats. It includes functions for checking and processing pedigree, calculating inbreeding coefficients (Meuwissen & Luo, 1992 <doi:10.1186/1297-9686-24-4-305>), as well as functions to calculate the matrix of genetic group contributions (Q), and adding those contributions to the genetic merit of animals (Quaas (1988) <doi:10.3168/jds.S0022-0302(88)79691-5>). Calculation of Q is computationally extensive. There are computationally optimized functions to calculate Q.

Works with 'ggplot2' to add a Van Gogh color palette to the user’s repertoire.
 It also has a function that work alongside 'ggplot2' to create more interesting data visualizations and add contextual information to the user’s plots.

Sankey and alluvial diagrams visualise flows of quantities across
    stages in stacked bars. This package makes it easy to create such
    diagrams using 'ggplot2'.

The function combines a scatter plot with ridgelines to better visualise the distribution between sample groups. The plot is created with 'ggplot2'.

Provides specialized visualization tools for Single-Case Experimental Design (SCED) 
    research using 'ggplot2'. SCED studies are a crucial methodology in behavioral and 
    educational research where individual participants serve as their own controls through 
    carefully designed experimental phases. This package extends 'ggplot2' to create 
    publication-ready graphics with professional phase change lines, support for multiple 
    baseline designs, and styling functions that follow SCED visualization conventions. 
    Key functions include adding phase change demarcation lines to existing plots and 
    formatting axes with broken axis appearance commonly used in single-case research.