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.

AuthorYan Jiao, Katherine Lawler, Andrew E Teschendorff, Charles Shijie Zheng
Date of publicationNone
MaintainerCharles Shijie Zheng <charles_zheng@live.com>
LicenseGPL-2
Version1.22.0

View on Bioconductor

Files in this package

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

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.