[HTML][HTML] Seqnet: An r package for generating gene-gene networks and simulating rna-seq data

T Grimes, S Datta�- Journal of statistical software, 2021 - ncbi.nlm.nih.gov
Journal of statistical software, 2021ncbi.nlm.nih.gov
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�…
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.
ncbi.nlm.nih.gov
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