An official website of the United States government
GSR: Simulator - SeqNet
| Attribute | Value |
|---|---|
| Title | SeqNet |
| Short Description | An R package for simulating RNA-seq counts from gene-gene association networks. |
| Long Description | Methods to generate random gene-gene association networks and simulate RNA-seq data from them, as described in Grimes and Datta (2021) . 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 | 1.1.3 |
| Project Started | 2021 |
| Last Release | 4 years, 1 month ago |
| Homepage | https://github.com/tgrimes/SeqNet |
| Citations | Grimes T, Datta S, SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data., J Stat Softw, July 1, 2021 [ Abstract, cited in PMC ] |
| GSR Certification |  ✔ Accessibility |
| Last evaluated | Feb. 14, 2022 (1284 days ago) |
| Author verification | The basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator. |
| Attribute Category | Attribute |
|---|---|
| Target | |
| Type of Simulated Data | RNA, |
| Variations | Other, |
| Simulation Method | |
| Input | |
| Data Type | |
| File format | |
| Output | |
| Data Type | |
| Sequencing Reads | |
| File Format | |
| Sample Type | |
| Phenotype | |
| Trait Type | |
| Determinants | |
| Evolutionary Features | |
| Demographic | |
| Population Size Changes | |
| Gene Flow | |
| Spatiality | |
| Life Cycle | |
| Mating System | |
| Fecundity | |
| Natural Selection | |
| Determinant | |
| Models | |
| Recombination | |
| Mutation Models | |
| Events Allowed | |
| Other | Phenogenetic, Polygenic background, |
| Interface | Command-line, |
| Development | |
| Tested Platforms | Windows, Mac OS X, |
| Language | C or C++, R, |
| License | GNU Public License, |
| GSR Certification | Accessibility, Documentation, Application, Support, |
Number of Primary Citations: 1
Number of Non-Primary Citations: 2
The following 2 publications are selected examples of applications that used SeqNet.
2023
Chen Y, Zhang XF, Ou-Yang L, Inferring cancer common and specific gene networks via multi-layer joint graphical model., Comput Struct Biotechnol J, Jan. 18, 2023 [Abstract]
Jiménez-Marín B, Rakijas JB, Tyagi A, Pandey A, Hanschen ER, Anderson J, Heffel MG, Platt TG, Olson BJSC, Gene loss during a transition to multicellularity., Sci Rep, March 31, 2023 [Abstract]