regNet: An R package for network-based propagation of gene expression alterations
CDS members associated with the software: Prof. Dr. Andreas Beyer
regNet is an R package that utilizes gene expression and copy number data to learn regulatory networks for the quantification of potential impacts of individual gene expression alterations on user-defined target genes via network propagation.
Gene expression alterations and potentially underlying gene copy number mutations can be measured routinely in the wet lab, but it is still extremely challenging to quantify impacts of altered genes on clinically relevant characteristics to predict putative driver genes. We developed the R package regNet that utilizes gene expression and copy number data to learn regulatory networks for the quantification of potential impacts of individual gene expression alterations on user-defined target genes via network propagation. We demonstrate the value of regNet by identifying putative major regulators that distinguish pilocytic from diffuse astrocytomas and by predicting putative impacts of glioblastoma-specific gene copy number alterations on cell cycle pathway genes and patient survival.
regNet is jointly developed with Dr. Michael Seifert from the TU Dresden.
Related publications:
- regNet: An R package for network-based propagation of gene expression alterations. Seifert M, Beyer A. Bioinformatics. 2017 Aug 31. doi: 10.1093/bioinformatics/btx544
- Importance of rare gene copy number alterations for personalized tumor characterization and survival analysis. Seifert M, Friedrich B, Beyer A. Genome Biol. 2016 Oct 3;17(1):204.