Root Expected Proportion Squared Difference (REPSD) is a nonparametric
  differential item functioning (DIF) method that (a) allows practitioners 
  to explore for DIF related to small, fine-grained focal groups of examinees, 
  and (b) compares the focal group directly to the composite group that will be 
  used to develop the reported test score scale. Using your provided response 
  matrix with a column that identifies focal group membership, this package
  provides the REPSD values, a simulated null distribution of possible REPSD
  values, and the simulated p-values identifying items possibly displaying DIF 
  without requiring enormous sample sizes.

Provides a collection of methods for quantifying representational similarity between learned features or multivariate data. The package offers an efficient 'C++' backend, designed for applications in machine learning, computational neuroscience, and multivariate statistics. See Klabunde et al. (2025) <doi:10.1145/3728458> for a comprehensive overview of the topic.

Predicting regulatory DNA elements based on epigenomic signatures. This package is more of a set of building blocks than a direct solution. REPTILE regulatory prediction pipeline is built on this R package. See <https://github.com/yupenghe/REPTILE> for more information.

Provides easy access to 'The Reptile Database', a comprehensive catalogue of all living reptile species and their classification. This package includes taxonomic data for over 10,000 reptile species, approximately 2,800 of which are subspecies, covering all extant reptiles. The dataset features taxonomic names, synonyms, distribution data, type specimens, and literature references, making it ready for research and analysis. Data is sourced from 'The Reptile Database' <http://www.reptile-database.org/>.

Recursive lists in the form of R objects, 'JSON', and 'XML',
    for use in teaching and examples. Examples include color palettes,
    Game of Thrones characters, 'GitHub' users and repositories, music
    collections, and entities from the Star Wars universe. Data from the
    'gapminder' package is also included, as a simple data frame and in
    nested and split forms.