A wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.
Version: 0.99.1 Depends: R (≥ 3.6.0) Imports: glmnet, survival, ggplot2, POT, parallel, utils, pbapply, methods, SummarizedExperiment Suggests: rmarkdown, knitr, rmdformats, qpdf Published: 2023-03-24 DOI: 10.32614/CRAN.package.VSOLassoBag Author: Jiaqi Liang [aut], Chaoye Wang [aut, cre] Maintainer: Chaoye Wang <wangcy1 at sysucc.org.cn> License: GPL-3 NeedsCompilation: no Materials: NEWS CRAN checks: VSOLassoBag results [issues need fixing before 2025-09-03] Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=VSOLassoBag to link to this page.
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