SeqNet: Generate RNA-Seq Data from Gene-Gene Association Networks

Methods to generate random gene-gene association networks and simulate RNA-seq data from them. Includes functions to generate random networks of any size and perturb them to obtain differential networks. Network objects are built from individual, overlapping modules that represent pathways. The resulting network has various topological properties that are characteristic of gene regulatory networks. RNA-seq data can be generated such that the association among gene expression profiles reflect the underlying network. A reference RNA-seq dataset can be provided to model realistic marginal distributions. Plotting functions are available to visualize a network, compare two networks, and compare the expression of two genes across multiple networks.

Version: 1.1.0
Depends: R (≥ 3.6.0)
Imports: fitdistrplus, ggplot2, grDevices, graphics, igraph, mvtnorm, purrr, RColorBrewer, tibble, Rcpp, rlang, stats, utils, methods
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat
Published: 2019-12-18
Author: Tyler Grimes [aut, cre], Somnath Datta [aut]
Maintainer: Tyler Grimes <tyler.grimes at>
License: GPL-2 | GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: SeqNet results


Reference manual: SeqNet.pdf
Package source: SeqNet_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: SeqNet_1.1.0.tgz, r-oldrel: SeqNet_1.1.0.tgz
Old sources: SeqNet archive

Reverse dependencies:

Reverse imports: dnapath


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