Mosaic plots in the 'ggplot2' framework. Mosaic
    plot functionality is provided in a single 'ggplot2' layer by calling
    the geom 'mosaic'.

Implements the generalized Gauss Markov regression, this is useful when both predictor and response have uncertainty attached to them and also when covariance within the predictor, within the response and between the predictor and the response is present. Base on the results published in guide ISO/TS 28037 (2010) <https://www.iso.org/standard/44473.html>.

Estimation of partial correlation matrix using ridge penalty 
    followed by thresholding and reestimation. Under multivariate Gaussian 
    assumption, the matrix constitutes an Gaussian graphical model (GGM).

Facilitates efficient visualization of Relative Synonymous Codon Usage patterns across species. Based on analytical outputs from 'codonW', 'MEGA', and 'Phylosuite', it supports multi-species 'RSCU' comparisons and allows users to explore visual analysis of structurally similar datasets.

A 'grammar of graphics' approach for visualizing summary statistics from multiple Genome-wide Association Studies (GWAS). It offers geneticists, bioinformaticians, and researchers a powerful yet flexible tool for illustrating complex genetic associations using data from various GWAS datasets. The visualizations can be extensively customized, facilitating detailed comparative analysis across different genetic studies. Reference: Uffelmann, E. et al. (2021) <doi:10.1038/s43586-021-00056-9>.

Create plots that combine a phylogeny and frequency dynamics.
    Phylogenetic input can be a generic adjacency matrix or a tree of class "phylo".
    Inspired by similar plots in publications of the labs of RE Lenski and JE
    Barrick. Named for HJ Muller (who popularised such plots) and H Wickham (whose
    code this package exploits).

It provides materials (i.e. 'serial axes' objects, Andrew's plot, various glyphs for scatter plot) to visualize high dimensional data.

Geometries to plot network objects with 'ggplot2'.