Visualization and quality control tools for large-scale multiplex tissue analysis in TissUUmaps3

Andrea Behanova, Christophe Avenel, Axel Andersson, Eduard Chelebian, Anna Klemm, Lina Wik, Arne Östman, Carolina Wählby
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引用次数: 1

Abstract

Abstract Large-scale multiplex tissue analysis aims to understand processes such as development and tumor formation by studying the occurrence and interaction of cells in local environments in, for example, tissue samples from patient cohorts. A typical procedure in the analysis is to delineate individual cells, classify them into cell types, and analyze their spatial relationships. All steps come with a number of challenges, and to address them and identify the bottlenecks of the analysis, it is necessary to include quality control tools in the analysis workflow. This makes it possible to optimize the steps and adjust settings in order to get better and more precise results. Additionally, the development of automated approaches for tissue analysis requires visual verification to reduce skepticism with regard to the accuracy of the results. Quality control tools could be used to build users’ trust in automated approaches. In this paper, we present three plugins for visualization and quality control in large-scale multiplex tissue analysis of microscopy images. The first plugin focuses on the quality of cell staining, the second one was made for interactive evaluation and comparison of different cell classification results, and the third one serves for reviewing interactions of different cell types.
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TissUUmaps3中大规模多重组织分析的可视化和质量控制工具
大规模多元组织分析旨在通过研究细胞在局部环境中的发生和相互作用,例如来自患者队列的组织样本,来了解肿瘤的发展和形成过程。在分析中一个典型的程序是描绘单个细胞,将它们分类为细胞类型,并分析它们的空间关系。所有的步骤都伴随着许多挑战,为了解决这些挑战并确定分析的瓶颈,有必要在分析工作流中包含质量控制工具。这使得优化步骤和调整设置成为可能,以便获得更好更精确的结果。此外,组织分析自动化方法的发展需要视觉验证,以减少对结果准确性的怀疑。质量控制工具可以用来建立用户对自动化方法的信任。在本文中,我们提出了三个插件可视化和质量控制的大规模显微图像多重组织分析。第一个插件专注于细胞染色质量,第二个插件用于不同细胞分类结果的交互评价和比较,第三个插件用于回顾不同细胞类型的相互作用。
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