DOI: 10.18129/B9.bioc.EnMCB    

This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see EnMCB.

Predicting Disease Progression Based on Methylation Correlated Blocks using Ensemble Models

Bioconductor version: 3.12

Creation of the correlated blocks using DNA methylation profiles. A stacked ensemble of machine learning models, which combined the support vector machine and elastic-net regression model, can be constructed to predict disease progression.

Author: Xin Yu

Maintainer: Xin Yu <whirlsyu at gmail.com>

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biocViews DNAMethylation, MethylationArray, Normalization, Software, SupportVectorMachine
Version 1.2.2
In Bioconductor since BioC 3.11 (R-4.0) (1 year)
License GPL-2
Depends R (>= 4.0)
Imports foreach, doParallel, parallel, stats, survivalROC, glmnet, rms, survivalsvm, ggplot2, minfi, IlluminaHumanMethylation450kanno.ilmn12.hg19, survival, utils
Suggests SummarizedExperiment, testthat, Biobase, survminer, affycoretools, knitr, plotROC, prognosticROC
BugReports https://github.com/whirlsyu/EnMCB/issues
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