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.

Version: 0.3.0
Depends: R (≥ 3.5.0)
Imports: Rcpp, MASS
LinkingTo: Rcpp, RcppArmadillo
Published: 2019-10-14
Author: Fei Zhou, Jie Ren, Xiaoxi Li, Cen Wu, Yu Jiang
Maintainer: Fei Zhou <feiz at ksu.edu>
BugReports: https://github.com/feizhoustat/interep/issues
License: GPL-2
URL: https://github.com/feizhoustat/interep
NeedsCompilation: yes
Materials: NEWS
CRAN checks: interep results

Downloads:

Reference manual: interep.pdf
Package source: interep_0.3.0.tar.gz
Windows binaries: r-devel: interep_0.3.0.zip, r-devel-gcc8: interep_0.3.0.zip, r-release: interep_0.3.0.zip, r-oldrel: interep_0.3.0.zip
OS X binaries: r-release: interep_0.3.0.tgz, r-oldrel: interep_0.3.0.tgz
Old sources: interep archive

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