fastJT: Efficient Jonckheere-Terpstra Test Statistics for Robust Machine Learning and Genome-Wide Association Studies

This 'Rcpp'-based package implements highly efficient functions for the calculation of the Jonckheere-Terpstra statistic. It can be used for a variety of applications, including feature selection in machine learning problems, or to conduct genome-wide association studies (GWAS) with multiple quantitative phenotypes. The code leverages 'OpenMP' directives for multi-core computing to reduce overall processing time.

Package details

AuthorJiaxing Lin [aut], Alexander Sibley [aut, cre], Ivo Shterev [aut], Kouros Owzar [aut]
MaintainerAlexander Sibley <dcibioinformatics@duke.edu>
LicenseGPL (>= 2)
Version1.0.8
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fastJT")

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fastJT documentation built on June 8, 2025, 11:01 a.m.