We developed scAtlasVAE, a deep-learning-based method to integrate large-scale single-cell RNA sequencing data. Using this tool, we established a comprehensive, million-scale, pan-disease human CD8+ T cell reference atlas, which incorporates information on transcriptomes and the diversity of the αβ T cell receptor repertoire.
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References
Zhang, N. & Bevan, M. J. CD8+ T cells: foot soldiers of the immune system. Immunity 35, 161–168 (2011). A review article that presents the phenotypic heterogeneity of CD8+ T cells.
Pai, J. A. & Satpathy, A. T. High-throughput and single-cell T cell receptor sequencing technologies. Nat. Methods 18, 881–892 (2021). This review article summarizes the single-cell technologies that enable transcriptomic and TCRαβ information to be captured at the single-cell level.
Wu, L. et al. huARdb: human Antigen Receptor database for interactive clonotype-transcriptome analysis at the single-cell level. Nucleic Acids Res 50, D1244–D1254 (2022). This paper describes the huAR database we established, which contains the collection of single-cell immune profiling datasets.
Hudson, D. et al. Can we predict T cell specificity with digital biology and machine learning? Nat. Rev. Immunol. 23, 511–521 (2023). A perspective article that discusses the potential of computational approaches for solving several fundamental questions in T cell biology.
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This is a summary of: Xue, Z. et al. Integrative mapping of human CD8+ T cells in inflammation and cancer. Nat. Methods https://doi.org/10.1038/s41592-024-02530-0 (2024).
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Human CD8+ T cell map with single-cell transcriptome and TCR information. Nat Methods 22, 239–240 (2025). https://doi.org/10.1038/s41592-024-02529-7
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DOI: https://doi.org/10.1038/s41592-024-02529-7
