This is a collection of R games and other funny stuff, such as the
    classic Mine sweeper and sliding puzzles.

Provides functions to have visualization and clean-up of enriched gene ontologies (GO) terms, 
    protein complexes and pathways (obtained from multiple databases) using 'ConsensusPathDB' 
    from gene set over-expression analysis. Performs clustering of pathway based on similarity 
    of over-expressed gene sets and visualizations similar to Ingenuity Pathway Analysis (IPA) 
    when up and down regulated genes are known. The methods are described in a paper currently
    submitted by Orecchioni et al, 2020 in Nanoscale.

Compute alpha and beta contributional diversity metrics,
    which is intended for linking taxonomic and functional microbiome
    data. See 'GitHub' repository for the tutorial:
    <https://github.com/gavinmdouglas/FuncDiv/wiki>. Citation: Gavin M.
    Douglas, Sunu Kim, Morgan G. I. Langille, B. Jesse Shapiro (2023)
    <doi:10.1093/bioinformatics/btac809>.

Provides functional control charts 
    for statistical process monitoring of functional data, 
    using the methods of Capezza et al. (2020) <doi:10.1002/asmb.2507>, 
    Centofanti et al. (2021) <doi:10.1080/00401706.2020.1753581>,
    Capezza et al. (2024) <doi:10.1080/00401706.2024.2327346>,
    Capezza et al. (2024) <doi:10.1080/00224065.2024.2383674>,
    Centofanti et al. (2022) <doi:10.48550/arXiv.2205.06256>.
    The package is thoroughly illustrated in the paper of 
    Capezza et al (2023) <doi:10.1080/00224065.2023.2219012>.

YACFP (Yet Another Convenience Function Package). get_age() is a fast & accurate tool for measuring fractional years between two dates. stale_package_check() tries to identify any library() calls to unused packages.

Statistical hypothesis testing methods for
 inferring model-free functional dependency using asymptotic
 chi-squared or exact distributions. Functional test
 statistics are asymmetric and functionally optimal, unique
 from other related statistics. Tests in this package reveal
 evidence for causality based on the causality-by-
 functionality principle. They include asymptotic functional
 chi-squared tests (Zhang & Song 2013) <doi:10.48550/arXiv.1311.2707>,
 an adapted functional chi-squared test (Kumar & Song 2022) 
 <doi:10.1093/bioinformatics/btac206>, 
 and an exact functional test (Zhong & Song 2019)
 <doi:10.1109/TCBB.2018.2809743> (Nguyen et al. 2020)
 <doi:10.24963/ijcai.2020/372>. The normalized functional
 chi-squared test was used by Best Performer 'NMSUSongLab'
 in HPN-DREAM (DREAM8) Breast Cancer Network Inference
 Challenges (Hill et al. 2016) <doi:10.1038/nmeth.3773>. A
 function index (Zhong & Song 2019)
 <doi:10.1186/s12920-019-0565-9> (Kumar et al. 2018)
 <doi:10.1109/BIBM.2018.8621502> derived from the
 functional test statistic offers a new effect size measure
 for the strength of functional dependency, a better
 alternative to conditional entropy in many aspects. For
 continuous data, these tests offer an advantage over
 regression analysis when a parametric functional form
 cannot be assumed; for categorical data, they provide a
 novel means to assess directional dependency not possible
 with symmetrical Pearson's chi-squared or Fisher's exact
 tests.