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Single-cell epigenomics

Discrete latent embeddings illuminate cellular diversity in single-cell epigenomics

CASTLE, a deep learning approach, extracts interpretable discrete representations from single-cell chromatin accessibility data, enabling accurate cell type identification, effective data integration, and quantitative insights into gene regulatory mechanisms.

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Fig. 1: Overview of the CASTLE framework for analyzing single-cell chromatin accessibility data.


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Correspondence to Zhi Wei.

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Wei, Z. Discrete latent embeddings illuminate cellular diversity in single-cell epigenomics. Nat Comput Sci 4, 316–317 (2024).

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