To install this package, start R and enter:
## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("FEM")
In most cases, you don't need to download the package archive at all.
FEM
Identification of Functional Epigenetic Modules
Bioconductor version: 3.1
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 Yinming Jiao
Maintainer: Andrew E. Teschendorff <andrew at picb.ac.cn>
Citation (from within R,
enter citation("FEM")):
Installation
To install this package, start R and enter:
## try http if https is not available
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")
| 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. | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, DifferentialMethylation, NetworkEnrichment, Software, SystemsBiology |
| Version | 2.2.1 |
| In Bioconductor since | BioC 3.0 (R-3.1) (1 year) |
| License | GPL (>=2) |
| Depends | AnnotationDbi, Matrix, marray, corrplot, igraph, impute, limma, org.Hs.eg.db |
| Imports | graph |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | FEM_2.2.1.tar.gz |
| Windows Binary | FEM_2.2.1.zip |
| Mac OS X 10.6 (Snow Leopard) | FEM_2.2.1.tgz |
| Mac OS X 10.9 (Mavericks) | FEM_2.2.1.tgz |
| Subversion source | (username/password: readonly) |
| Git source | https://github.com/Bioconductor-mirror/FEM/tree/release-3.1 |
| Package Short Url | http://bioconductor.org/packages/FEM/ |
| Package Downloads Report | Download Stats |
Documentation »
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