Learn R Programming

DART (version 1.20.0)

Denoising Algorithm based on Relevance network Topology

Description

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.

Copy Link

Version

Monthly Downloads

12

Version

1.20.0

License

GPL-2

Maintainer

Charles Shijie Zheng

Last Published

February 15th, 2017

Functions in DART (1.20.0)

PredActScore

Computes the DART activation score of the model signature in the samples of a data set.
DoDART

Main function of DART
dataDART

Example data for DART package
PruneNet

Prunes relevance network to allow only edges that are consistent with the predictions of the model signature
DoDARTCLQ

Improved edition of DoDART
EvalConsNet

Evaluates the consistency of the inferred relevance correlation network with the correlations predicted by the model pathway signature.
BuildRN

Builds the relevance correlation network
DART-package

Denoising Algorithm based on Relevance network Topology