preprint · bioRxiv (Cold Spring Harbor Laboratory) · 2024

Decoding cell identity with multi-scale explainable deep learning

Jun Zhu, Zeyang Zhang, Zeyang Zhang, Yujia Xiang, Beini Xie, Xinwen Dong, Linhai Xie, Peijie Zhou, Rongyan Yao, Xiaowen Wang, Yang Li, Fuchu He, Wenwu Zhu, Ziwei Zhang, Ziwei Zhang, Cheng Chang

Cited by 3Open access

Abstract

Abstract Cells are the fundamental structural and functional units of life. Studying the definition and composition of different cell types can help us understand the complex mechanisms underlying biological diversity and functionality. The increasing volume of extensive single-cell omics data makes it possible to provide detailed characterisations of cell types. Recently, there has been a rise in deep learning-based approaches that generate cell type labels solely through mapping query data to reference data. However, these approaches lack multi-scale descriptions and interpretations of identified cell types. Here, we propose Cell Decoder, a biological prior knowledge informed model to achieve multi-scale representation of cells. We implemented automated machine learning and post-hoc analysis techniques to decode cell identity. We have shown that Cell Decoder compares favourably to existing methods, offering multi-view interpretability for decoding cell identity and data integration. Furthermore, we have showcased its applicability in uncovering novel cell types and states in both human bone and mouse embryonic contexts, thereby revealing the multi-scale heterogeneity inherent in cell identities.

Cite this paper

APA 7

Zhu, J., Zhang, Z., Zhang, Z., Xiang, Y., Xie, B., Dong, X., Xie, L., Zhou, P., Yao, R., Wang, X., Li, Y., He, F., Zhu, W., Zhang, Z., Zhang, Z., & Chang, C. (2024). Decoding cell identity with multi-scale explainable deep learning. bioRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2024.02.05.578922

MLA 9

Zhu, Jun, et al. “Decoding cell identity with multi-scale explainable deep learning.” bioRxiv (Cold Spring Harbor Laboratory), 2024, https://doi.org/10.1101/2024.02.05.578922.

Chicago

Zhu, Jun, Zeyang Zhang, Zeyang Zhang, Yujia Xiang, Beini Xie, Xinwen Dong, Linhai Xie, et al. 2024. “Decoding cell identity with multi-scale explainable deep learning.” bioRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2024.02.05.578922.

Harvard

Zhu, J. et al. (2024) ‘Decoding cell identity with multi-scale explainable deep learning’, bioRxiv (Cold Spring Harbor Laboratory). Available at: https://doi.org/10.1101/2024.02.05.578922.

BibTeX

@misc{zhu2024decoding,
  title = {{Decoding cell identity with multi-scale explainable deep learning}},
  author = {Zhu, Jun and Zhang, Zeyang and Zhang, Zeyang and Xiang, Yujia and Xie, Beini and Dong, Xinwen and Xie, Linhai and Zhou, Peijie and Yao, Rongyan and Wang, Xiaowen and Li, Yang and He, Fuchu and Zhu, Wenwu and Zhang, Ziwei and Zhang, Ziwei and Chang, Cheng},
  journal = {bioRxiv (Cold Spring Harbor Laboratory)},
  year = {2024},
  doi = {10.1101/2024.02.05.578922}
}

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