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scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

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scAR install with bioconda code style: black Documentation Status semantic-release: angular test Stars Downloads

scAR (single-cell Ambient Remover) is a tool designed for denoising ambient signals in droplet-based single-cell omics data. It can be employed for a wide range of applications, such as, sgRNA assignment in scCRISPRseq, identity barcode assignment in cell indexing, protein denoising in CITE-seq, mRNA denoising in scRNAseq, and ATAC signal denoising in scATACseq, among others.

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Dependencies

PyTorch 1.8 Python 3.8.6 torchvision 0.9.0 tqdm 4.62.3 scikit-learn 1.0.1

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License

This project is licensed under the terms of License.
Copyright 2022 Novartis International AG.

Reference

If you use scAR in your research, please consider citing our manuscript,

@article {Sheng2022.01.14.476312,
	author = {Sheng, Caibin and Lopes, Rui and Li, Gang and Schuierer, Sven and Waldt, Annick and Cuttat, Rachel and Dimitrieva, Slavica and Kauffmann, Audrey and Durand, Eric and Galli, Giorgio G and Roma, Guglielmo and de Weck, Antoine},
	title = {Probabilistic modeling of ambient noise in single-cell omics data},
	elocation-id = {2022.01.14.476312},
	year = {2022},
	doi = {10.1101/2022.01.14.476312},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {https://www.biorxiv.org/content/early/2022/01/14/2022.01.14.476312},
	eprint = {https://www.biorxiv.org/content/early/2022/01/14/2022.01.14.476312.full.pdf},
	journal = {bioRxiv}
}