GRN-guided in silico simulation of single-cell RNA-seq data using Causal Generative Adversarial Networks
Implementation of GRouNdGAN as described in:
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
Simulated dataset and their underlying ground truth GRNs are available for download on our website.
For a detailed tutorial and comprehensive API references, please visit our project's documentation here.
@article{zinati2024groundgan,
title={GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks},
author={Zinati, Yazdan and Takiddeen, Abdulrahman and Emad, Amin},
journal={Nature Communications},
volume={15},
number={1},
pages={1--18},
year={2024},
publisher={Nature Publishing Group}
}
Copyright (C) 2023 Emad's COMBINE Lab: Yazdan Zinati, Abdulrahman Takiddeen, and Amin Emad.
GRouNdGAN is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
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You should have received a copy of the GNU Affero General Public License along with GRouNdGAN. If not, see https://www.gnu.org/licenses/.