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fastJT: Efficient Jonckheere-Terpstra Test Statistics

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: 1.0.6
Imports: Rcpp (≥ 0.12.3)
LinkingTo: Rcpp
Suggests: knitr
Published: 2020-11-10
DOI: 10.32614/CRAN.package.fastJT
Author: Jiaxing Lin, Alexander Sibley, Ivo Shterev, and Kouros Owzar
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:

Reference manual: fastJT.pdf
Vignettes: fastJT

Downloads:

Package source: fastJT_1.0.6.tar.gz
Windows binaries: r-devel: fastJT_1.0.6.zip, r-release: fastJT_1.0.6.zip, r-oldrel: fastJT_1.0.6.zip
macOS binaries: r-release (arm64): fastJT_1.0.6.tgz, r-oldrel (arm64): fastJT_1.0.6.tgz, r-release (x86_64): fastJT_1.0.6.tgz, r-oldrel (x86_64): fastJT_1.0.6.tgz
Old sources: fastJT archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=fastJT to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.