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Provides a framework for high-dimensional mediation analysis using transfer learning. The main function TransHDM() integrates large-scale source data to improve the detection power of potential mediators in small-sample target studies. It addresses data heterogeneity via transfer regularization and debiased estimation while controlling the false discovery rate. The package also includes utilities for data generation (gen_simData_homo(), gen_simData_hetero()), baseline methods such as lasso() and dblasso(), sure independence screening via SIS(), and model diagnostics through source_detection(). The methodology is described in Pan et al. (2025) <doi:10.1093/bib/bbaf460>.
| Version: | 1.1.3 |
| Depends: | R (≥ 4.0.0) |
| Imports: | glmnet (≥ 4.1-10), caret (≥ 7.0-1), MASS (≥ 7.3-61), doParallel (≥ 1.0.17), foreach (≥ 1.5.2), HDMT (≥ 1.0.5), ggplot2 (≥ 3.4.0) |
| Suggests: | knitr (≥ 1.50), rmarkdown (≥ 2.30), spelling (≥ 2.3.2), dplyr (≥ 1.0.0), tidyr (≥ 1.0.0), ggrepel (≥ 0.9.0) |
| Published: | 2026-08-20 |
| DOI: | 10.32614/CRAN.package.TransHDM |
| Author: | Huer Gao [aut, cre, cph], Lulu Pan [aut, cph], Yongfu Yu [ctb, cph], Guoyou Qin [ctb, cph] |
| Maintainer: | Huer Gao <26111020050 at m.fudan.edu.cn> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/Gaohuer/TransHDM |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | TransHDM citation info |
| CRAN checks: | TransHDM results |
| Reference manual: | TransHDM.html , TransHDM.pdf |
| Vignettes: |
TransHDM: High-Dimensional Mediation Analysis via Transfer Learning (source, R code) |
| Package source: | TransHDM_1.1.3.tar.gz |
| Windows binaries: | r-devel: TransHDM_1.0.1.zip, r-release: TransHDM_1.1.3.zip, r-oldrel: TransHDM_1.1.3.zip |
| macOS binaries: | r-release (arm64): TransHDM_1.1.3.tgz, r-oldrel (arm64): TransHDM_1.1.3.tgz, r-release (x86_64): TransHDM_1.1.3.tgz, r-oldrel (x86_64): TransHDM_1.1.3.tgz |
| Old sources: | TransHDM archive |
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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.