An R package for simulating RNA-seq counts from gene-gene association networks. Long Description (required)
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. https://github.com/tgrimes/SeqNet u241918@bcm.edu
Step 1: Use the attribute tree to add new attributes or remove pre-selected attributes to describe the simulator.
Every sub-attribute is selected Not all sub-attributes are selectedFill Clear Expand Collapse Reset
Summary of Proposed Changes Step 2: Review list of proposed attribute addition(s) and subtraction(s).
Can't Find the Attribute You Are Looking For? If you would like to propose an attribute that you cannot find in the tree above, or if you would like to add a clarification to one or more attributes for this simulator (e.g. a specific file format for attribute /Output/File Format/Other), please list them in the Additional Comment box of the Submit tab .
Summary of Proposed Changes Current Citations/Applications
[Pubmed ID: 34321962 ],
Grimes T, Datta S ,
SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data. ,
J Stat Softw ,
07-01-2021 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=34321962, Primary Citation
[Pubmed ID: 36733706 ],
Chen Y, Zhang XF, Ou-Yang L ,
Inferring cancer common and specific gene networks via multi-layer joint graphical model. ,
Comput Struct Biotechnol J ,
01-18-2023 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=36733706, , Application
[Pubmed ID: 37002250 ],
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 ,
03-31-2023 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=37002250, , Application