EnMCB

DOI: 10.18129/B9.bioc.EnMCB  

Predicting Disease Progression Based on Methylation Correlated Blocks using Ensemble Models

Bioconductor version: Release (3.16)

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>

Installation

To install this package, start R (version "4.2") 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

PDF		Reference Manual

Details

biocViews	DNAMethylation, MethylationArray, Normalization, Software, SupportVectorMachine
Version	1.10.0
In Bioconductor since	BioC 3.11 (R-4.0) (3 years)
License	GPL-2
Depends	R (>= 4.0)
Imports	methods, stats, survivalROC, glmnet, rms, mboost, Matrix, igraph, survivalsvm, ggplot2, BiocFileCache, boot, e1071, survival, utils
LinkingTo
Suggests	SummarizedExperiment, testthat, Biobase, survminer, affycoretools, knitr, plotROC, minfi, limma, rmarkdown
SystemRequirements
Enhances
URL
BugReports	https://github.com/whirlsyu/EnMCB/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package
Windows Binary	EnMCB_1.10.0.zip (64-bit only)
macOS Binary (x86_64)	EnMCB_1.10.0.tgz
macOS Binary (arm64)	EnMCB_1.10.0.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