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.
| Version: |
1.0.8 |
| Imports: |
Rcpp (≥ 0.12.3) |
| LinkingTo: |
Rcpp |
| Suggests: |
knitr |
| Published: |
2025-05-01 |
| Author: |
Jiaxing Lin [aut],
Alexander Sibley [aut, cre],
Ivo Shterev [aut],
Kouros Owzar [aut] |
| Maintainer: |
Alexander Sibley <dcibioinformatics at duke.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Citation: |
fastJT citation info |
| Materials: |
NEWS |
| CRAN checks: |
fastJT results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=fastJT
to link to this page.