A torch-based integration method for single-cell multi-omic data.
Project description
MIDAS: a deep generative model for mosaic integration and knowledge transfer of single-cell multimodal data.
MIDAS turns mosaic data into imputed and batch-corrected data to support single-cell multimodal analysis.
Read our paper at Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS.
Read our documentation at https://scmidas.readthedocs.io/en/latest/.
Installation
conda create -n scmidas python=3.12
conda activate scmidas
conda install scmidas
or:
pip install scmidas
🔥New
- MIDAS supports not only RNA, ADT, and ATAC data but also allows seamless integration of additional modalities with straightforward configuration.
- Leverages PyTorch Lightning for efficient training, including advanced strategies such as distributed data parallel (DDP).
- Integrates with TensorBoard for real-time visualization and tracking of training metrics, such as loss.
Reproducibility
Refer to https://github.com/labomics/midas/tree/reproducibility/.
Citation
If you use MIDAS in your work, please cite the midas publication as follows:
@article{he2024mosaic,
title={Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS},
author={He, Zhen and Hu, Shuofeng and Chen, Yaowen and An, Sijing and Zhou, Jiahao and Liu, Runyan and Shi, Junfeng and Wang, Jing and Dong, Guohua and Shi, Jinhui and others},
journal={Nature Biotechnology},
pages={1--12},
year={2024},
publisher={Nature Publishing Group US New York}
}
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