Full descriptive statistics, physical description of sediment,
            metric or phi sieves. Includes a Shiny web application for
            interactive grain size analysis and visualization.

Interface for 'g3-lollipop' 'JavaScript' library.
    Visualize genetic mutation data using an interactive lollipop diagram in 'RStudio' or your web browser.

Create stunning network experiences powered by the 'G6' graph visualisation engine
    'JavaScript' library <https://g6.antv.antgroup.com/en>. In 'shiny' mode, modify your
    graph directly from the server function to dynamically interact with nodes and edges.
    Select your favorite layout among 20 choices. 15 behaviors are available such as
    interactive edge creation, collapse-expand and brush select.
    17 plugins designed to improve the user experience such as a mini-map,
    toolbars and grid lines. Customise the look and feel of your graph with comprehensive
    options for nodes, edges and more.

Flexible general-purpose toolbox implementing genetic 
  algorithms (GAs) for stochastic optimisation. Binary, real-valued, and
  permutation representations are available to optimize a fitness 
  function, i.e. a function provided by users depending on their 
  objective function. Several genetic operators are available and can be
  combined to explore the best settings for the current task. 
  Furthermore, users can define new genetic operators and easily 
  evaluate their performances. Local search using general-purpose 
  optimisation algorithms can be applied stochastically to exploit 
  interesting regions. GAs can be run sequentially or in parallel, using
  an explicit master-slave parallelisation or a coarse-grain islands 
  approach. For more details see Scrucca (2013) 
  <doi:10.18637/jss.v053.i04> and Scrucca (2017) 
  <doi:10.32614/RJ-2017-008>.

This is a companion to Henry-Stewart talk by Zhao (2026, <doi:10.69645/FRFQ9519>),
 which gathers information, metadata and scripts to showcase modern genetic analysis -- ranging from testing
 of polymorphic variant(s) for Hardy-Weinberg equilibrium, association with traits using genetic and statistical
 models, Bayesian implementation, power calculation in study design, and genetic annotation. It also covers
 R integration with the Linux environment, GitHub, package creation and web applications. The earlier version
 by Zhao (2009, <doi:10.69645/DCRY5578>) provides an brief introduction to these topics.