Reconstruct pedigrees from genotype data, by optimising the
    likelihood over all possible pedigrees subject to given restrictions.
    Tailor-made plots facilitate evaluation of the output. This package is
    part of the 'pedsuite' ecosystem for pedigree analysis. In
    particular, it imports 'pedprobr' for calculating pedigree likelihoods
    and 'forrel' for estimating pairwise relatedness.

Tools for exchanging pedigree data between the 'pedsuite'
    packages and the 'Familias' software for forensic kinship computations
    (Egeland et al. (2000) <doi:10.1016/s0379-0738(00)00147-x>). These
    functions were split out from the 'forrel' package to streamline
    maintenance and provide a lightweight alternative for packages otherwise
    independent of 'forrel'.

Gene-level variant association tests with disease status for pedigree data: kernel and burden association statistics.

Tools to sort, edit and prune pedigrees and to extract the inbreeding coefficients
    and the relationship matrix (includes code for pedigrees from self-pollinated species). 
    The use of pedigree data is central to genetics research within the animal and plant breeding communities to predict 
    breeding values. The relationship matrix between the individuals can be derived from pedigree structure 
    ('Vazquez et al., 2010') <doi:10.2527/jas.2009-1952>.

Generate Mermaid syntax for a pedigree flowchart from a pedigree data frame.
    Mermaid syntax is commonly used to generate plots, charts, diagrams, and flowcharts. It is a textual syntax for creating reproducible illustrations. This package generates Mermaid syntax from a pedigree data frame to visualize a pedigree flowchart. The Mermaid syntax can be embedded in a Markdown or R Markdown file, or viewed on Mermaid editors and renderers. Links' shape, style, and orientation can be customized via function arguments, and nodes' shapes and styles can be customized via optional columns in the pedigree data frame.

A collection of functions for modelling mutations in
    pedigrees with marker data, as used e.g. in likelihood computations
    with microsatellite data. Implemented models include equal,
    proportional and stepwise models, as well as random models for
    experimental work, and custom models allowing the user to apply any
    valid mutation matrix. Allele lumping is done following the
    lumpability criteria of Kemeny and Snell (1976), ISBN:0387901922.