To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("RTN")

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

RTN

Reconstruction of transcriptional networks and analysis of master regulators

Bioconductor version: 3.1

This package provides classes and methods for transcriptional network inference and analysis. Modulators of transcription factor activity are assessed by conditional mutual information, and master regulators are mapped to phenotypes using different strategies, e.g., gene set enrichment, shadow and synergy analyses. Additionally, master regulators can be linked to genetic markers using eQTL/VSE analysis, taking advantage of the haplotype block structure mapped to the human genome in order to explore risk-associated SNPs identified in GWAS studies.

Author: Mauro Castro, Xin Wang, Michael Fletcher, Florian Markowetz and Kerstin Meyer

Maintainer: Mauro Castro <mauro.a.castro at gmail.com>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("RTN")

Documentation

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

browseVignettes("RTN")

 

PDF R Script Main vignette: reconstruction and analysis of transcriptional networks in R
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneExpression, GeneRegulation, GeneSetEnrichment, GeneticVariability, GraphAndNetwork, NetworkAnalysis, NetworkEnrichment, NetworkInference, SNP, Software
Version 1.6.2
In Bioconductor since BioC 2.13 (R-3.0) (2 years)
License Artistic-2.0
Depends R (>= 2.15), methods, igraph
Imports RedeR, minet, snow, limma, data.table, ff, car, IRanges
LinkingTo
Suggests HTSanalyzeR, RUnit, BiocGenerics
SystemRequirements
Enhances
URL http://dx.doi.org/10.1038/ncomms3464
Depends On Me Fletcher2013b
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source RTN_1.6.2.tar.gz
Windows Binary RTN_1.6.2.zip
Mac OS X 10.6 (Snow Leopard) RTN_1.6.2.tgz
Mac OS X 10.9 (Mavericks) RTN_1.6.2.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/RTN/tree/release-3.1
Package Short Url http://bioconductor.org/packages/RTN/
Package Downloads Report Download Stats

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