interep: Interaction Analysis of Repeated Measure Data
Version 0.1.0

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. A new upgraded version will be released in the near future. 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.

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Package details

AuthorFei Zhou, Yinhao Du, Jie Ren, Xiaoxi Li, Cen Wu
Date of publication2018-09-03 12:30:13 UTC
MaintainerFei Zhou <[email protected]>
Package repositoryView on CRAN
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interep documentation built on Sept. 3, 2018, 5:03 p.m.