DART: Denoising Algorithm based on Relevance network Topology

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.

Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("DART")
AuthorYan Jiao, Katherine Lawler, Andrew E Teschendorff, Charles Shijie Zheng
Bioconductor views DifferentialExpression GeneExpression GraphAndNetwork Pathways
Date of publicationNone
MaintainerCharles Shijie Zheng <charles_zheng@live.com>
LicenseGPL-2
Version1.24.0

View on Bioconductor

Files

DESCRIPTION
NAMESPACE
R
R/BuildRN.R R/DoDART.R R/DoDARTCLQ.R R/EvalConsNet.R R/PredActScore.R R/PruneNet.R
build
build/vignette.rds
data
data/dataDART.rda
data/datalist
inst
inst/CITATION
inst/NEWS
inst/doc
inst/doc/DART.R
inst/doc/DART.Rnw
inst/doc/DART.pdf
man
man/BuildRN.Rd man/DART-package.Rd man/DoDART.Rd man/DoDARTCLQ.Rd man/EvalConsNet.Rd man/PredActScore.Rd man/PruneNet.Rd man/dataDART.Rd
vignettes
vignettes/DART.Rnw

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