Package: VSOLassoBag
Type: Package
Title: Variable Selection Oriented LASSO Bagging Algorithm
Version: 0.99.1
Date: 2023-3-24
biocViews: Software, StatisticalMethod, FeatureExtraction
Authors@R: c(
  person('Jiaqi', 'Liang',  email = 'liangjq27@mail2.sysu.edu.cn', role = c('aut')),
  person('Chaoye', 'Wang',  email = 'wangcy1@sysucc.org.cn', role = c('aut', 'cre'))
  )
Description: 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.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: glmnet, survival, ggplot2, POT, parallel, utils, pbapply,
        methods, SummarizedExperiment
RoxygenNote: 7.2.0
Suggests: rmarkdown, knitr, rmdformats, qpdf
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2023-03-24 16:11:44 UTC; zhou
Author: Jiaqi Liang [aut],
  Chaoye Wang [aut, cre]
Maintainer: Chaoye Wang <wangcy1@sysucc.org.cn>
Repository: CRAN
Date/Publication: 2023-03-24 16:40:08 UTC
Built: R 4.2.3; ; 2024-04-24 01:59:30 UTC; windows
