细胞空间分析:使用多范围、多类型点过程模型学习细胞类型空间关系。
CytoSpatio: Learning cell type spatial relationships using multirange, multitype point process models.
作者信息
Chen Haoran, Murphy Robert F
机构信息
Computational Biology Department, School of Computer Science, Carnegie Mellon University.
出版信息
bioRxiv. 2024 Nov 3:2024.10.31.621408. doi: 10.1101/2024.10.31.621408.
Recent advances in multiplexed fluorescence imaging have provided new opportunities for deciphering the complex spatial relationships among various cell types across diverse tissues. We introduce CytoSpatio, open-source software that constructs generative, multirange, and multitype point process models that capture interactions among multiple cell types at various distances simultaneously. On analyzing five cell types across five tissues, our software showed consistent spatial relationships within the same tissue type, with certain cell types like proliferating T cells consistently clustering across tissue types. It also revealed that the attraction-repulsion relationships between cell types like B cells and CD4-positive T cells vary with tissue type. CytoSpatio can also generate synthetic tissue structures that preserve the spatial relationships seen in training images, a capability not provided by previous descriptive, motif-based approaches. This potentially allows spatially realistic simulations of how cell relationships affect tissue biochemistry.
多重荧光成像技术的最新进展为解读不同组织中各种细胞类型之间复杂的空间关系提供了新机遇。我们推出了CytoSpatio,这是一款开源软件,它构建生成性、多范围和多类型点过程模型,可同时捕捉多种细胞类型在不同距离下的相互作用。在分析五种组织中的五种细胞类型时,我们的软件显示同一组织类型内存在一致的空间关系,某些细胞类型(如增殖性T细胞)在不同组织类型中持续聚类。它还揭示了B细胞和CD4阳性T细胞等细胞类型之间的吸引 - 排斥关系随组织类型而变化。CytoSpatio还可以生成保留训练图像中所见空间关系的合成组织结构,这是以前基于描述性基序的方法所不具备的能力。这有可能实现对细胞关系如何影响组织生物化学的空间真实模拟。