SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data

J Stat Softw. 2021 Jul;98(12):10.18637/jss.v098.i12. doi: 10.18637/jss.v098.i12. Epub 2021 Jul 10.

Abstract

Gene expression data provide an abundant resource for inferring connections in gene regulatory networks. While methodologies developed for this task have shown success, a challenge remains in comparing the performance among methods. Gold-standard datasets are scarce and limited in use. And while tools for simulating expression data are available, they are not designed to resemble the data obtained from RNA-seq experiments. SeqNet is an R package that provides tools for generating a rich variety of gene network structures and simulating RNA-seq data from them. This produces in silico RNA-seq data for benchmarking and assessing gene network inference methods. The package is available on CRAN and on GitHub at https://github.com/tgrimes/SeqNet.

Keywords: Gaussian graphical model; Gene regulatory networks; co-expression methods; differential network analysis.