Package: fastJT 1.0.8
Alexander Sibley
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.
Authors:
fastJT_1.0.8.tar.gz
fastJT_1.0.8.zip(r-4.7)fastJT_1.0.8.zip(r-4.6)fastJT_1.0.8.zip(r-4.5)
fastJT_1.0.8.tgz(r-4.6-x86_64)fastJT_1.0.8.tgz(r-4.6-arm64)fastJT_1.0.8.tgz(r-4.5-x86_64)fastJT_1.0.8.tgz(r-4.5-arm64)
fastJT_1.0.8.tar.gz(r-4.7-arm64)fastJT_1.0.8.tar.gz(r-4.7-x86_64)fastJT_1.0.8.tar.gz(r-4.6-arm64)fastJT_1.0.8.tar.gz(r-4.6-x86_64)
fastJT_1.0.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fastJT/json (API)
NEWS
| # Install 'fastJT' in R: |
| install.packages('fastJT', repos = c('https://dcibioinformatics.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:74dc52592f. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 125 | ||
| linux-devel-x86_64 | OK | 120 | ||
| source / vignettes | OK | 167 | ||
| linux-release-arm64 | OK | 110 | ||
| linux-release-x86_64 | OK | 108 | ||
| macos-release-arm64 | OK | 115 | ||
| macos-release-x86_64 | OK | 330 | ||
| macos-oldrel-arm64 | OK | 141 | ||
| macos-oldrel-x86_64 | OK | 258 | ||
| windows-devel | OK | 95 | ||
| windows-release | OK | 115 | ||
| windows-oldrel | OK | 111 | ||
| wasm-release | OK | 89 |
Exports:fastJTfastJT.selectpvaluessummary.fastJT
Dependencies:Rcpp
