Abstract
Motivation: Inferring large scale directional networks with higher accuracy has important applications such as gene regulatory network or finance.
Results: We modified a well-established conservative causal core network inference algorithm, C3NET, to be able to infer very large scale networks with direction information. This advanced version is called Ac3net. We demonstrate that Ac3net outperforms C3NET and many other popular algorithms when considering the directional interaction information of gene/protein networks. We provide and R package and present performance results that are reproducible via the Supplementary file.
Availability: Ac3net is available on CRAN and at github.com/altayg/Ac3net
Contact: altay{at}lji.org
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Posted March 02, 2018.
