论文信息 - GNET2: an R package for constructing gene regulatory networks from transcriptomic data.

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

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.

[1] Gary Stacey,et al. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data , 2013, BMC Bioinformatics.

[2] Guy Karlebach,et al. Modelling and analysis of gene regulatory networks , 2008, Nature Reviews Molecular Cell Biology.

[3] Damian Szklarczyk,et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets , 2018, Nucleic Acids Res..

[4] Trupti Joshi,et al. Reconstructing differentially co-expressed gene modules and regulatory networks of soybean cells , 2012, BMC Genomics.

[5] D. Pe’er,et al. Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data , 2003, Nature Genetics.

[6] B. Katzenellenbogen,et al. Transcriptomic analysis identifies gene networks regulated by estrogen receptor α (ERα) and ERβ that control distinct effects of different botanical estrogens , 2014, Nuclear receptor signaling.