Probabilistic Integrative Networks is a set of Python and R scripts for generating network from RNA-Seq data which involves finding differentially expressed genes, data augmentation, computing dependency relationships, merging networks probabilistically developed by Haluk Dogan, Zeynep Hakguder, Roland Madadjim, Stephen Scott and Juan Cui, in the Department of Computer Science and Engineering, University of Nebraska-Lincoln.
PIN is open-source software made available under the terms of the The GNU Common Public License v.3.0. You are free to use the code under those terms.
Visualization of Final Models
Stage 1
2500 nodes, 9522 edges, average degree of 7.6176
Stage 2
2500 nodes, 9578 edges, average degree of 7.6624
Stage 3
2500 nodes, 9877 edges, average degree of 7.9016
Stage 4
2500 nodes, 9749 edges, average degree of 7.7992
