Computes a novel metric of affinity between two entities based on their co-occurrence 
  (using binary presence/absence data). The metric and its MLE, alpha hat, were advanced in 
  Mainali, Slud, et al, 2021 <doi:10.1126/sciadv.abj9204>. Various types of confidence intervals and median interval
  were developed in Mainali and Slud, 2022 <doi:10.1101/2022.11.01.514801>.

Generate project files and directories following a pre-made template.
  You can specify variables to customize file names and content, and
  flexibly adapt the template to your needs. 'cookiecutter' for 'R'
  implements a subset of the excellent 'cookiecutter' package for the
  'Python' programming language (<https://github.com/cookiecutter/>), and
  aims to be largely compatible with the original 'cookiecutter' template
  format.

A convenient tool to store and format browser cookies and use them 
    in 'HTTP' requests (for example, through 'httr2', 'httr' or 'curl').

Browser cookies are name-value pairs that are saved in a
    user's browser by a website. Cookies allow websites to persist
    information about the user and their use of the website. Here we
    provide tools for working with cookies in 'shiny' apps, in part by
    wrapping the 'js-cookie' JavaScript library
    <https://github.com/js-cookie/js-cookie>.

Implementing the computational phase of the Causes of Outcome Learning approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. 2022. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. International Journal of Epidemiology <doi:10.1093/ije/dyac078>. The optional 'ggtree' package can be obtained through Bioconductor.

Collection of routines for efficient scientific computations in physics and astrophysics. These routines include utility functions, numerical computation tools, as well as visualisation tools. They can be used, for example, for generating random numbers from spherical and custom distributions, information and entropy analysis, special Fourier transforms, two-point correlation estimation (e.g. as in Landy & Szalay (1993) <doi:10.1086/172900>), binning & gridding of point sets, 2D interpolation, Monte Carlo integration, vector arithmetic and coordinate transformations. Also included is a non-exhaustive list of important constants and cosmological conversion functions. The graphics routines can be used to produce and export publication-ready scientific plots and movies, e.g. as used in Obreschkow et al. (2020, MNRAS Vol 493, Issue 3, Pages 4551–4569). These routines include special color scales, projection functions, and bitmap handling routines.