Constructs gene regulatory networks from single-cell gene expression data using the PANDA (Passing Attributes between Networks for Data Assimilation) algorithm.

An accurate and easy tool for performing linear trajectory inference on
  single cells using single-cell RNA sequencing data. In addition, 'SCORPIUS'
  provides functions for discovering the most important genes with respect to
  the reconstructed trajectory, as well as nice visualisation tools.
  Cannoodt et al. (2016) <doi:10.1101/079509>.

Perform the balanced (Scott and Knott, 1974) and unbalanced <doi:10.1590/1984-70332017v17n1a1> Scott & Knott algorithm.

The Scott-Knott Effect Size Difference (ESD) test is a mean comparison approach that leverages a hierarchical clustering to partition the set of treatment means (e.g., means of variable importance scores, means of model performance) into statistically distinct groups with non-negligible difference [Tantithamthavorn et al., (2018) <doi:10.1109/TSE.2018.2794977>].

Implements the Scout method for regression, described in "Covariance-regularized regression and classification for high-dimensional problems", by Witten and Tibshirani (2008),  Journal of the Royal Statistical Society, Series B 71(3): 615-636.

Creates a contextual menu that can be triggered with keyboard shortcuts or programmatically.
    This can replace traditional sidebars or navigation bars, thereby enhancing the 
    user experience with lighter user interfaces.

Using principal component analysis as a base model, 'SCOUTer' 
    offers a new approach to simulate outliers in a simple and precise way. 
    The user can generate new observations defining them by a pair of well-known 
    statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2) 
    statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer' 
    returns a new set of observations with the desired target properties. 
    Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and 
    Alberto Ferrer (2020).