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 from the Comprehensive R Archive Network at https://CRAN.R-project.org/package= SeqNet and on GitHub at https://github.com/tgrimes/SeqNet.
CITATION STYLE
Grimes, T., & Datta, S. (2021). Seqnet: An r package for generating gene-gene networks and simulating rna-seq data. Journal of Statistical Software, 98(12), 1–49. https://doi.org/10.18637/jss.v098.i12
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