GNET2: an R package for constructing gene regulatory networks from transcriptomic data

Abstract

Motivation: The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use.

Results: Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets.

Availability and implementation: The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2.

Supplementary information: Supplementary data are available at Bioinformatics online.