Provides the alpha-adjustment correction from "Benjamini, Y., & Hochberg, Y. (1995) <doi:10.1111/j.2517-6161.1995.tb02031.x> Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1), 289-300". For researchers interested in using the exact mathematical formulas and procedures as used in the original paper.

Provides algorithms for frequency-based pairing of alpha-beta T
  cell receptors.

Computation of the alpha-shape and alpha-convex
        hull of a given sample of points in the plane. The concepts of
        alpha-shape and alpha-convex hull generalize the definition of
        the convex hull of a finite set of points. The programming is
        based on the duality between the Voronoi diagram and Delaunay
        triangulation. The package also includes a function that
        returns the Delaunay mesh of a given sample of points and its
        dual Voronoi diagram in one single object.

Sets the alpha level for coefficients in a regression model
    as a decreasing function of the sample size through the use of
    Jeffreys' Approximate Bayes factor. You tell alphaN() your sample
    size, and it tells you to which value you must lower alpha to avoid
    Lindley's Paradox. For details, see Wulff and Taylor (2024)
    <doi:10.1177/14761270231214429>.

Given the parameters of a distribution, the package uses the concept of alpha-outliers by Davies and Gather (1993) to flag outliers in a data set. See Davies, L.; Gather, U. (1993): The identification of multiple outliers, JASA, 88 423, 782-792, <doi:10.1080/01621459.1993.10476339> for details.

A software that implements a method for partitioning genetic trends to
    quantify the sources of genetic gain in breeding programmes.
    The partitioning method is described in Garcia-Cortes et al.
    (2008) <doi:10.1017/S175173110800205X>. The package includes the
    main function AlphaPart for partitioning breeding values and auxiliary
    functions for manipulating data and summarizing, visualizing, and saving
    results.