DART

Denoising Algorithm based on Relevance network Topology

Bioconductor version: Release (2.14)

Denoising Algorithm based on Relevance network Topology (DART) is an algorithm designed to evaluate the consistency of prior information molecular signatures (e.g in-vitro perturbation expression signatures) in independent molecular data (e.g gene expression data sets). If consistent, a pruning network strategy is then used to infer the activation status of the molecular signature in individual samples.

Author: Yan Jiao, Katherine Lawler, Andrew E Teschendorff

Maintainer: Katherine Lawler <katherine.lawler at kcl.ac.uk>

To install this package, start R and enter:

    source("http://bioconductor.org/biocLite.R")
    biocLite("DART")

To cite this package in a publication, start R and enter:

    citation("DART")

Documentation

PDF R Script DART Tutorial
PDF   Reference Manual
Text   NEWS

Details

biocViews DifferentialExpression, GeneExpression, GraphAndNetwork, Pathways, Software
Version 1.10.0
In Bioconductor since BioC 2.10 (R-2.15)
License GPL-2
Depends R (>= 2.10.0), igraph (>= 0.6.0)
Imports
Suggests breastCancerVDX, breastCancerMAINZ, Biobase
System Requirements
URL
Depends On Me
Imports Me
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Package Downloads

Package Source DART_1.10.0.tar.gz
Windows Binary DART_1.10.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) DART_1.10.0.tgz
Mac OS X 10.9 (Mavericks)
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