cran. To fix this you can add URL: https://cran.r-universe.dev/interep to the package DESCRIPTION file. See also theR-universe documentation.Package: interep 0.4.1
Fei Zhou
interep: Interaction Analysis of Repeated Measure Data
Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. The core module of this package is developed in C++. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.
Authors:
interep_0.4.1.tar.gz
interep_0.4.1.tar.gz(r-4.7-arm64)interep_0.4.1.tar.gz(r-4.7-x86_64)interep_0.4.1.tar.gz(r-4.6-arm64)interep_0.4.1.tar.gz(r-4.6-x86_64)
interep_0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
interep/json (API)
NEWS
| # Install 'interep' in R: |
| install.packages('interep', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/feizhoustat/interep/issues
- dat - Simulated data for demonstrating the features of interep
Last updated from:d17d77bfb3. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 120 | ||
| linux-devel-x86_64 | OK | 109 | ||
| source / vignettes | OK | 217 | ||
| linux-release-arm64 | OK | 122 | ||
| linux-release-x86_64 | OK | 153 | ||
| wasm-release | OK | 104 |
Exports:cv.interepdmcpintereppenaltyreformat
Dependencies:MASSRcppRcppArmadillo
