It aggregates protein panel data and metadata for protein quantitative
 trait locus (pQTL) analysis using 'pQTLtools' (<https://jinghuazhao.github.io/pQTLtools/>).
 The package includes data from affinity-based panels such as 'Olink' (<https://olink.com/>) 
 and 'SomaScan' (<https://somalogic.com/>), as well as mass spectrometry-based panels from
 'CellCarta' (<https://cellcarta.com/>) and 'Seer' (<https://seer.bio/>). The metadata
 encompasses updated annotations and publication details.

Data analysis for Project Risk Management via the Second Moment Method, 
  Monte Carlo Simulation, Contingency Analysis, Sensitivity Analysis, Earned Value Management, 
  Learning Curves, Design Structure Matrices, and more.

Quickly and easily generate plots of acoustic data aligned with transcriptions similar to those made in 'Praat' using either derived signals generated directly in R with 'wrassp' or imported derived signals from 'Praat'. Provides easy and fast out-of-the-box solutions but also a high extent of  flexibility. Also provides options for embedding audio in figures and animating figures.

Distance-based parametric bootstrap tests for clustering with 
  spatial neighborhood information. Some distance measures, 
  Clustering of presence-absence, abundance and multilocus genetic data 
  for species delimitation, nearest neighbor 
  based noise detection. Genetic distances between communities.
  Tests whether various distance-based regressions
  are equal. Try package?prabclus for on overview.

Provides a large number of functions from numerical analysis and
    linear algebra, numerical optimization, differential equations,
    time series, plus some well-known special mathematical functions.
    Uses 'MATLAB' function names where appropriate to simplify porting.

Streamline the creation of 'Docker' images with 'R' packages and dependencies embedded. The 'pracpac' package provides a 'usethis'-like interface to creating Dockerfiles with dependencies managed by 'renv'. The 'pracpac' functionality is described in Nagraj and Turner (2023) <doi:10.48550/arXiv.2303.07876>.