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Realize three approaches for Gene-Environment interaction analysis. All of them adopt Sparse Group Minimax Concave Penalty to identify important G variables and G-E interactions, and simultaneously respect the hierarchy between main G and G-E interaction effects. All the three approaches are available for Linear, Logistic, and Poisson regression. Also realize to mine and construct prior information for G variables and G-E interactions.
| Version: | 1.0 |
| Imports: | MASS, glmnet, stats, rvest, dplyr, pheatmap, grDevices, graphics |
| Published: | 2022-01-10 |
| Author: | Xiaoyan Wang, Hongduo Liu, and Shuangge Ma |
| Maintainer: | Xiaoyan Wang <xywang at hnu.edu.cn> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| CRAN checks: | GEInfo results |
| Reference manual: | GEInfo.pdf |
| Package source: | GEInfo_1.0.tar.gz |
| Windows binaries: | r-devel: GEInfo_1.0.zip, r-release: GEInfo_1.0.zip, r-oldrel: GEInfo_1.0.zip |
| macOS binaries: | r-release (arm64): GEInfo_1.0.tgz, r-oldrel (arm64): GEInfo_1.0.tgz, r-release (x86_64): GEInfo_1.0.tgz, r-oldrel (x86_64): GEInfo_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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