To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("FEM")

In most cases, you don't need to download the package archive at all.

FEM

DOI: 10.18129/B9.bioc.FEM    

Identification of Functional Epigenetic Modules

Bioconductor version: Release (3.5)

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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("FEM")

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 3.4.0
In Bioconductor since BioC 3.0 (R-3.1) (3 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
Build Report  

Package Archives

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

Source Package FEM_3.4.0.tar.gz
Windows Binary FEM_3.4.0.zip
Mac OS X 10.11 (El Capitan) FEM_3.4.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/FEM
Package Short Url http://bioconductor.org/packages/FEM/
Package Downloads Report Download Stats

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