Provides the ability to create interaction maps, discover CNV map domains (edges), gene annotate interactions, and create interactive visualizations of these CNV interaction maps.

Coalescent simulators can rapidly simulate biological sequences
    evolving according to a given model of evolution.
    You can use this package to specify such models, to conduct the simulations
    and to calculate additional statistics from the results (Staab, Metzler,
    2016 <doi:10.1093/bioinformatics/btw098>).
    It relies on existing simulators for doing the simulation, and currently
    supports the programs 'ms', 'msms' and 'scrm'. It also supports finite-sites
    mutation models by combining the simulators with the program 'seq-gen'.
    Coala provides functions for calculating certain summary statistics, which
    can also be applied to actual biological data.
    One possibility to import data is through the 'PopGenome' package
    (<https://github.com/pievos101/PopGenome>).

Flexible framework for coalescent analyses in R. It includes a main function running the  MCMC algorithm, auxiliary functions for tree rearrangement, and some functions to compute population genetic parameters. Extended description can be found in Paradis (2020) <doi:10.1201/9780429466700>. For details on the MCMC algorithm, see Kuhner et al. (1995) <doi:10.1093/genetics/140.4.1421> and Drummond et al. (2002) <doi:10.1093/genetics/161.3.1307>.

Estimates phylogenetic trees from allele count data using the root distance method under the Coalescent Model. Given a matrix of allele counts across taxa and loci, the package estimates pairwise root distances under the Coalescent Model using maximum likelihood estimation. Then, it estimates a labeled phylogenetic tree from the estimated root distances. See Peng et al. (2021) <doi:10.1016/j.ympev.2021.107142>.

An implementation of a Bayesian framework for the opinion poll
    based estimation of event probabilities in multi-party electoral systems
    (Bender and Bauer (2018) <doi:10.21105/joss.00606>).