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相关概念视频

Flow Cytometry01:23

Flow Cytometry

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The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
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Sample Preparation for Mass Cytometry Analysis
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CytoNormPy 能够快速且可扩展地删除细胞测量数据集中的批量效应

Tarik Exner1,2, Nicolaj Hackert1,2, Luca Leomazzi3,4

  • 1Internal Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
|August 29, 2025
PubMed
概括

我们开发了CytoNormPy, 这是一个更快的Python实现CytoNorm算法, 该工具增强了用于临床诊断和研究的细胞计量数据分析.

关键词:
其他:在 Python 中批量纠正细胞测量

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科学领域:

  • 生物医学数据分析
  • 计算生物学
  • 免疫学

背景情况:

  • 细胞计量对于临床诊断,研究和研究至关重要.
  • 技术变化的批量影响使细胞计量数据分析复杂化.
  • 对于可靠的结果来说,对批量效应的考虑是必不可少的.

研究的目的:

  • 介绍CytoNorm算法的Python实现,用于删除批量效应.
  • 为现有实施提供更快,更兼容的替代方案.
  • 通过集群算法和可视化扩展功能.

主要方法:

  • 开发了CytoNormPy,这是CytoNorm 2.0的Python实现.
  • 集成的共同集群算法.
  • 包括用于算法评估的关键可视化.

主要成果:

  • 与R相比,CytoNormPy的性能提高了85%.
  • 该实现与常见的Python单单元数据结构兼容.
  • 增加了包括集群和可视化在内的新功能.

结论:

  • CytoNormPy提供了一种高效和多功能解决方案,用于对细胞测量数据进行批量效应校正.
  • 该工具有助于在临床和基础研究中进行更强大的分析.
  • 免费可用的实施促进了更广泛的采用和可重复性.