Generates interactive Jellyfish plots to visualize spatiotemporal tumor
    evolution by integrating sample and phylogenetic trees into a unified plot.
    This approach provides an intuitive way to analyze tumor heterogeneity and
    evolution over time and across anatomical locations. The Jellyfish plot
    visualization design was first introduced by Lahtinen, Lavikka, et al.
    (2023, <doi:10.1016/j.ccell.2023.04.017>).
    This package also supports visualizing ClonEvol results, a tool developed
    by Dang, et al. (2017, <doi:10.1093/annonc/mdx517>), for analyzing clonal
    evolution from multi-sample sequencing data. The 'clonevol' package is not
    available on CRAN but can be installed from its GitHub
    repository (<https://github.com/hdng/clonevol>).

Fast extrapolation of univariate and multivariate time features using K-Nearest Neighbors. The compact set of hyper-parameters is tuned via grid or random search.

Manage project dependencies from your DESCRIPTION file. Create a reproducible virtual environment with minimal additional files in your project. Provides tools to add, remove, and update dependencies as well as install existing dependencies with a single function.

The goal of 'jetty' is to execute R functions and code
    snippets in an isolated R subprocess within a 'Docker' container
    and return the evaluated results to the local R session. 'jetty'
    can install necessary packages at runtime and seamlessly propagates
    errors and outputs from the 'Docker' subprocess back to the main
    session. 'jetty' is primarily designed for sandboxed testing and
    quick execution of example code.

Estimates networks of conditional dependencies (Gaussian graphical models) from multiple classes of data (similar but not exactly, i.e. measurements on different equipment, in different locations or for various sub-types). Package also allows to generate simulation data and evaluate the performance. Implementation of the method described in Angelini, De Canditiis and Plaksienko (2022) <doi:10.3390/math10213983>.