Plot brain atlases as interactive 3D meshes using 'Three.js'
    via 'htmlwidgets', or render publication-quality static images through
    'rgl' and 'rayshader'. A pipe-friendly API lets you map data onto
    brain regions, control camera angles, toggle region edges, overlay
    glass brains, and snapshot or ray-trace the result. Additional
    atlases are available through the 'ggsegverse' r-universe. Mowinckel
    & Vidal-Piñeiro (2020) <doi:10.1177/2515245920928009>.

It provides a better alternative for stacked bar plot by creating a segmented total bar plot with custom annotations and labels. It is useful for visualizing the total of a variable and its segments in a single bar, making it easier to compare the segments and their contributions to the total.

Provides an interactive workflow for visualizing structural equation modeling (SEM), multi-group path diagrams, and network diagrams in R. Users can directly manipulate nodes and edges to create publication-quality figures while maintaining statistical model integrity. Supports integration with 'lavaan', 'OpenMx', 'tidySEM', and 'blavaan' etc. Features include parameter-based aesthetic mapping, generative AI assistance, and complete reproducibility by exporting metadata for script-based workflows.

The extensive range of functions provided by this package makes it possible to draw highly versatile sequence logos. Features include, but not limited to, modifying colour schemes and fonts used to draw the logo, generating multiple logo plots, and aiding the visualisation with annotations. Sequence logos can easily be combined with other plots 'ggplot2' plots.

A set of wrapper functions that mainly re-produces most of the 
  sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base 
  R to produce the plots this library draws on 'ggplot2'. 
  The plots are produced on the basis of a sequence object defined  
  with TraMineR::seqdef(). The package automates the reshaping and plotting 
  of sequence data. Resulting plots are of class 'ggplot', i.e. components 
  can be added and tweaked using '+' and regular 'ggplot2' functions.