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Distinguish direct and indirect interactions with Graphical Modelling

Bioconductor version: 2.13

Distinguish direct from indirect interactions in gene regulation and infer combinatorial code from highly correlated variables such as transcription factor binding profiles. The package implements the Neighbourhood Consistent PC algorithm (NCPC) and draws Direct Dependence Graphs to represent dependence structure around a target variable. The package also provides a unified interface to other Graphical Modelling (Bayesian Network) packages for distinguishing direct and indirect interactions.

Author: Robert Stojnic

Maintainer: Robert Stojnic <robert.stojnic at>

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PDF ddgraph-cluster.pdf
PDF ddgraph-ddgraph-plot.pdf
PDF R Script Overview of the 'ddgraph' package
PDF   Reference Manual
Text   NEWS


biocViews Bioinformatics, GraphsAndNetworks, Software
Version 1.6.3
In Bioconductor since BioC 2.11 (R-2.15)
License GPL-3
Depends graph, methods, Rcpp
Imports bnlearn (>= 2.8), gtools, pcalg, RColorBrewer, plotrix, MASS, Rcpp
Suggests testthat, Rgraphviz, e1071, ROCR, testthat
System Requirements
Depends On Me
Imports Me
Suggests Me

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