Performs copy number variants association analysis with Lasso and Weighted Fusion penalized regression. 
  Creates a "CNV profile curve" to represent an individual’s CNV events across a genomic region so to capture variations 
  in CNV length and dosage. When evaluating association, the CNV profile curve is directly used as a predictor in the 
  regression model, avoiding the need to predefine CNV loci. CNV profile regression estimates CNV effects at each genome
  position, making the results comparable across different studies. The penalization encourages sparsity 
  in variable selection with a Lasso penalty and encourages effect smoothness between consecutive CNV events with a weighted
  fusion penalty, where the weight controls the level of smoothing between adjacent CNVs. 
  For more details, see Si (2024) <doi:10.1101/2024.11.23.624994>.

Implements Dirichlet multinomial modeling of relative abundance data using functionality provided by the 'Stan' software. The purpose of this package is to provide a user friendly way to interface with 'Stan' that is suitable for those new to modeling. For more regarding the modeling mathematics and computational techniques we use see our publication in Molecular Ecology Resources titled 'Dirichlet multinomial modeling outperforms alternatives for analysis of ecological count data' (Harrison et al. 2020 <doi:10.1111/1755-0998.13128>).

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>).