To identify tumor-driving active regulatory circuits, we propose a Bioconductor (Huber et al., 2015) package named CoRegNet to (i) reconstruct a large-scale co-regulatory network from gene expression data and by integrating additional regulatory evidences such as TF Binding site and ChIP data, (ii) estimate the activity of each TF of the network in any given sample, (iii) predict sets of cooperative TF and (iv) identify sample-specific combination of active and driver TF using an interactive visualization tool integrating genomic aberrations. This evidence concerns the gene TF and neoplasm.