dyngen is a novel, multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. dyngen is more flexible than current single-cell simulation engines, and allows better method development and benchmarking, thereby stimulating development and testing of novel computational methods.
dyngen is now published (CC-BY,
doi:10.1038/s41467-021-24152-2).
Run citation("dyngen") to obtain the corresponding citation
information. All source code for reproducing the results in this
manuscript are available on
GitHub.
dyngen should work straight out of the CRAN box by running
install.packages("dyngen"). Having said that, you should definitely
configure a few system variables for optimal speed. Check the
installation
guide for more
information!
Check out this guide on how to get started with dyngen. You can find more guides by clicking any of the links below:
- Getting started
- Installation instructions
- Showcase different backbones
- Advanced: Comparison to reference dataset
- Advanced: Constructing a custom backbone
- Advanced: Running dyngen from a docker container
- Advanced: On scalability and runtime
- Advanced: Simulating batch effects
- Advanced: Simulating a knockout experiment
- Advanced: Tweaking parameters
A full list of changes is available on our changelog.