Provides a minimal, light-weight set of tools for producing nice looking maps in R, with support for map projections.  See Brown (2016) <doi:10.32614/RJ-2016-005>.

Visualise admixture as pie charts on a projected map, admixture as traditional structure barplots or facet barplots, and scatter plots from genotype principal components analysis. A 'shiny' app allows users to create admixture maps interactively. Jenkins TL (2024) <doi:10.1111/1755-0998.13943>.

Topological data analysis (TDA) is a method of data analysis that 
  uses techniques from topology to analyze high-dimensional data. Here we
  implement Mapper, an algorithm from this area developed by Singh, Mémoli and 
  Carlsson (2007) which generalizes the concept of a 
  Reeb graph <https://en.wikipedia.org/wiki/Reeb_graph>.

The Mapper algorithm from Topological Data Analysis, the steps are as follows 1. Define a filter (lens) function on the data. 2. Perform clustering within each level set. 3. Generate a complex from the clustering results.

Easily create functions to map between different sets of values,
  such as for re-labelling categorical variables.

Create simple maps; add sub-plots like pie plots to a map or any other plot; format, plot and export gridded data. The package was developed for displaying fisheries data but most functions can be used for more generic data visualisation.

Construction of genetic maps in autopolyploid full-sib populations. 
             Uses pairwise recombination fraction estimation as the first 
             source of information to sequentially position allelic variants 
             in specific homologous chromosomes. For situations where pairwise 
             analysis has limited power, the algorithm relies on the multilocus 
             likelihood obtained through a hidden Markov model (HMM). 
             For more detail, please see  Mollinari and Garcia (2019) 
             <doi:10.1534/g3.119.400378> and Mollinari et al. (2020) 
             <doi:10.1534/g3.119.400620>.

Provides one function, which is a wrapper around purrr::map() with some extras on top, including parallel computation, progress bars, error handling, and result caching.