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
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:

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