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, Charles Shijie Zheng|
|Bioconductor views||DifferentialExpression GeneExpression GraphAndNetwork Pathways|
|Date of publication||None|
|Maintainer||Charles Shijie Zheng <firstname.lastname@example.org>|
BuildRN: Builds the relevance correlation network
DART-package: Denoising Algorithm based on Relevance network Topology
dataDART: Example data for DART package
DoDART: Main function of DART
DoDARTCLQ: Improved edition of DoDART
EvalConsNet: Evaluates the consistency of the inferred relevance...
PredActScore: Computes the DART activation score of the model signature in...
PruneNet: Prunes relevance network to allow only edges that are...
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