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, Alexander Sibley, Ivo Shterev, and Kouros Owzar
MaintainerJiaxing Lin <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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fastJT documentation built on Aug. 15, 2017, 1:01 a.m.