FEM

DOI: 10.18129/B9.bioc.FEM    

This package is for version 3.10 of Bioconductor; for the stable, up-to-date release version, see FEM.

Identification of Functional Epigenetic Modules

Bioconductor version: 3.10

The FEM package performs a systems-level integrative analysis of DNA methylation and gene expression data. It seeks modules of functionally related genes which exhibit differential promoter DNA methylation and differential expression, where an inverse association between promoter DNA methylation and gene expression is assumed. For full details, see Jiao et al Bioinformatics 2014.

Author: Andrew E. Teschendorff and Zhen Yang

Maintainer: Zhen Yang <yangzhen at picb.ac.cn>

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

Installation

To install this package, start R (version "3.6") and enter:

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

BiocManager::install("FEM")

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("FEM")

 

PDF R Script The FEM package performs a systems-level integrative analysis of DNA methylationa and gene expression. It seeks modules of functionally related genes which exhibit differential promoter DNA methylation and differential expression, where an inverse association between promoter DNA methylation and gene expression is assumed. For full details, see Jiao et al Bioinformatics 2014.
PDF   Reference Manual

Details

biocViews DifferentialExpression, DifferentialMethylation, NetworkEnrichment, Software, SystemsBiology
Version 3.14.0
In Bioconductor since BioC 3.0 (R-3.1) (5.5 years)
License GPL (>=2)
Depends AnnotationDbi, Matrix, marray, corrplot, igraph, impute, limma, org.Hs.eg.db, graph, BiocGenerics
Imports graph
LinkingTo
Suggests
SystemRequirements
Enhances
URL
Depends On Me ChAMP
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package FEM_3.14.0.tar.gz
Windows Binary FEM_3.14.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) FEM_3.14.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/FEM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/FEM
Package Short Url https://bioconductor.org/packages/FEM/
Package Downloads Report Download Stats

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