EnMCB

Predicting Disease Progression Based on Methylation Correlated Blocks using Ensemble Models


Bioconductor version: Release (3.19)

Creation of the correlated blocks using DNA methylation profiles. Machine learning models can be constructed to predict differentially methylated blocks and disease progression.

Author: Xin Yu

Maintainer: Xin Yu <whirlsyu at gmail.com>

Citation (from within R, enter citation("EnMCB")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("EnMCB")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("EnMCB")
vignette HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DNAMethylation, MethylationArray, Normalization, Software, SupportVectorMachine
Version 1.16.0
In Bioconductor since BioC 3.11 (R-4.0) (4.5 years)
License GPL-2
Depends R (>= 4.0)
Imports survivalROC, glmnet, rms, mboost, Matrix, igraph, methods, survivalsvm, ggplot2, boot, e1071, survival, BiocFileCache
System Requirements
URL
Bug Reports https://github.com/whirlsyu/EnMCB/issues
See More
Suggests SummarizedExperiment, testthat, Biobase, survminer, affycoretools, knitr, plotROC, limma, rmarkdown
Linking To
Enhances
Depends On Me
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Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package EnMCB_1.16.0.tar.gz
Windows Binary EnMCB_1.16.0.zip
macOS Binary (x86_64) EnMCB_1.16.0.tgz
macOS Binary (arm64) EnMCB_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/EnMCB
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/EnMCB
Bioc Package Browser https://code.bioconductor.org/browse/EnMCB/
Package Short Url https://bioconductor.org/packages/EnMCB/
Package Downloads Report Download Stats