Welcome to GRouNdGAN’s documentation!#
This site documents the code released under GRouNdGAN (GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks). GRouNdGAN is a gene regulatory network (GRN)-guided causal implicit generative model for simulating single-cell RNA-seq data, in-silico perturbation experiments, and benchmarking GRN inference methods.
To find out more details about GRouNdGAN, check out our paper:
Zinati, Y., Takiddeen, A. & Emad, A. GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks. Nat Commun 15, 4055 (2024). https://doi.org/10.1038/s41467-024-48516-6.
Contact#
Have a Question or Found a Bug?
We’re here to help!
Asking Questions:
If you have any questions, whether they’re about how to use our software, troubleshooting, or understanding certain concepts, please don’t hesitate to ask by contacting Yazdan Zinati.
Reporting Bugs:
If you encounter any issues, glitches, or unexpected behavior while using our software, please let us know. Reporting bugs helps us improve GRouNdGAN.
You can reach out to us by opening an issue on our GitHub repository.