This package provides methods to identify active transcriptional programs. Methods and classes are provided to import or infer large scale co-regulatory network from transcriptomic data. The specificity of the encoded networks is to model Transcription Factor cooperation. External regulation evidences (TFBS, ChIP,...) can be integrated to assess the inferred network and refine it if necessary. Transcriptional activity of the regulators in the network can be estimated using an measure of their influence in a given sample. Finally, an interactive UI can be used to navigate through the network of cooperative regulators and to visualize their activity in a specific sample or subgroup sample. The proposed visualization tool can be used to integrate gene expression, transcriptional activity, copy number status, sample classification and a transcriptional network including co-regulation information.
|Author||Remy Nicolle, Thibault Venzac and Mohamed Elati|
|Date of publication||None|
|Maintainer||Remy Nicolle <email@example.com>|
addEvidences: Integration of regulatory evidences.
coregnet: Initialize a co-regulatory network object.
CoRegNet-class: Class coregnet - Specifying the structure of the network used...
coRegnet-package: coRegnet : inference and interrogation co-regulation networks
coregulators: Extract all co-regulators of a regulatory network.
discretizeExpressionData: Three-value discretization of gene expression data.
display: Display a shiny interactive web interface to
hLICORN: Hybrid Learning of co-operative regulation network.
HumanDataExamples: Human Transcription Factor data and Bladder cancer dataset.
HumanTF: List of Human Transcription Factors.
masterRegulator: Identify phenotype related Master Regulators.
refine: Refine an inferred regulatory network using external...
regulatorInfluence: Regulator Influence, estimating the sample specific activity...
regulators: Interogate a coregnet object.
summary: Summaries and info coregnet