A universal single-cell atlas decodes pulmonary diseases
编号:68 访问权限:仅限参会人 更新:2025-03-25 14:40:45 浏览:26次 口头报告

报告开始:2025年03月30日 10:00(Asia/Shanghai)

报告时间:20min

所在会场:[S7] 前沿论坛 (基因组大数据与AI) [s7] 前沿论坛(基因组大数据与AI)

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摘要
Human lung is a complex organ susceptible to various diseases. Single-cell transcriptomic studies provide rich data for addressing specific research questions. Here, we present uniLUNG, the largest lung transcriptomic cell atlas, comprising over 10 million cells across 20 disease and healthy groups. By assembling a universal hierarchical annotation framework and performing a comprehensive data integration benchmarking, we established standardized lung cell nomenclature and marker genes. Using uniLUNG, we identified Lym-monocytes and T-like B cells, new cell types in certain lung diseases, confirming their existence by comparing with external single-cell atlases. Additionally, we discovered the NSCLC-like SCLC, a transitional malignant cell population related to NSCLC-to-SCLC transition, which was validated and characterized in spatial dimensions, revealing its complex role in tumour progression. Overall, uniLUNG provides an extensive representation of human lung cell diversity and serves as an invaluable data resource and a solid foundation for lung research.
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报告人
李伟忠
教授 中山大学医学院

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重要日期
  • 会议日期

    03月28日

    2025

    03月30日

    2025

  • 04月15日 2025

    注册截止日期

主办单位
中国生物信息学学会基因组信息学专业委员会
承办单位
中国农业科学院农业基因组研究所
大鹏湾实验室
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