Provides bindings to 'Tree-sitter', an incremental parsing
    system for programming tools. 'Tree-sitter' builds concrete syntax
    trees for source files of any language, and can efficiently update
    those syntax trees as the source file is edited. It also includes a
    robust error recovery system that provides useful parse results even
    in the presence of syntax errors.

Provides bindings to a 'C' grammar for Tree-sitter, to be used
    alongside the 'treesitter' package. Tree-sitter builds concrete syntax trees
    for source files and can efficiently update them or generate code like producing 
    R C API wrappers from C functions, structs and global definitions from header files.

Provides bindings to an 'R' grammar for 'Tree-sitter', to be
    used alongside the 'treesitter' package. 'Tree-sitter' builds concrete
    syntax trees for source files of any language, and can efficiently
    update those syntax trees as the source file is edited.

Provide a range of functions with multiple criteria for cutting phylogenetic trees at any evolutionary depth. It enables users to cut trees in any orientation, such as rootwardly (from root to tips) and tipwardly (from tips to its root), or allows users to define a specific time interval of interest. It can also be used to create multiple tree pieces of equal temporal width. Moreover, it allows the assessment of novel temporal rates for various phylogenetic indexes, which can be quickly displayed graphically.

Tools for the exploration of distributions of phylogenetic trees.
    This package includes a 'shiny' interface which can be started from R using
    treespaceServer(). 
    For further details see Jombart et al. (2017) <DOI:10.1111/1755-0998.12676>.

Implements the tree-spatial scan statistic for detecting clusters
    that combine both spatial and hierarchical structures, as proposed by
    Cancado et al. (2025) <doi:10.1007/s10651-025-00670-w>. The method extends
    Kulldorff (1997) <doi:10.1080/03610929708831995> circular spatial scan
    statistic and the tree-based scan statistic of Kulldorff et al. (2003)
    <doi:10.1111/1541-0420.00039> by searching for anomalies in both
    geographic regions and branches of hierarchical trees simultaneously. The
    package also provides standalone implementations of Kulldorff's circular
    spatial scan statistic and the tree-based scan statistic. Statistical
    significance is assessed via Monte Carlo simulation under a Poisson or
    binomial model, with optional 'OpenMP' parallelization.