Statistical testing procedures for detecting
  GxE (gene-environment) interactions. The main focus lies on
  GRSxE interaction tests that aim at detecting GxE interactions
  through GRS (genetic risk scores). Moreover, a novel testing
  procedure based on bagging and OOB (out-of-bag) predictions is
  implemented for incorporating all available observations at
  both GRS construction and GxE testing (Lau et al., 2023,
  <doi:10.1038/s41598-023-28172-4>).

Functions to generate and analyze data for psychology experiments based on the General Recognition Theory.

Offers functions for the comparison of Gutenberg-Richter 
	b-values. Several functions in GRTo are helpful for the assessment of the
	quality of seismicity catalogs.

River hydrograph separation and daily runoff time series analysis. Provides
  various filters to separate baseflow and quickflow. Implements advanced separation 
  technique by Rets et al. (2022) <doi:10.1134/S0097807822010146> which involves 
  meteorological data to reveal genetic components of the runoff: ground, rain, thaw 
  and spring (seasonal thaw). High-performance C++17 computation, annually aggregated 
  variables, statistical testing and numerous plotting functions for high-quality 
  visualization.

A tool to sensitivity analysis using SOBOL (Sobol, 1993) and AMA (Dell'Oca et al. 2017 <doi:10.5194/hess-21-6219-2017>) indices.
            It allows to identify the most sensitive parameter or parameters of a model.

Provides utility functions used by the Genome Analysis Toolkit ('GATK') to load tables and plot data. The 'GATK' is a toolkit for variant discovery in high-throughput sequencing data.

Computing Global Sensitivity Indices from given data using Optimal Transport, as defined in Borgonovo et al (2024) <doi:10.1287/mnsc.2023.01796>. You provide an input sample, an output sample, decide the algorithm, and compute the indices.

Computation of Quantitative Trait Loci hits in the selected gene set. Performing gene set validation with Quantitative Trait Loci information. Performing gene set enrichment analysis with available Quantitative Trait Loci data and computation of statistical significance value from gene set analysis. Obtaining the list of Quantitative Trait Loci hit genes along with their overlapped Quantitative Trait Loci names.