Package: VSOLassoBag 0.99.1

VSOLassoBag: Variable Selection Oriented LASSO Bagging Algorithm

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.

Authors:Jiaqi Liang [aut], Chaoye Wang [aut, cre]

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4 exports 0.00 score 63 dependencies 4 scripts 242 downloads

Last updated 1 years agofrom:c87efe23dd. Checks:OK: 5 NOTE: 2. Indexed: yes.

Exports:kneedleLessPermutationsimpleEstimationVSOLassoBag

Dependencies:abindaskpassBiobaseBiocGenericsclicodetoolscolorspacecrayoncurlDelayedArrayfansifarverforeachGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2glmnetgluegtablehttrIRangesisobanditeratorsjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpbapplypillarpkgconfigPOTR6RColorBrewerRcppRcppEigenrlangS4ArraysS4VectorsscalesshapeSparseArraySummarizedExperimentsurvivalsystibbleUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc