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EzColocalization: An ImageJ plugin for visualizing and measuring colocalization in cells and organisms

机译:EzColocalization:一个ImageJ插件用于可视化和测量细胞和生物体中的共定位

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摘要

Insight into the function and regulation of biological molecules can often be obtained by determining which cell structures and other molecules they localize with (i.e. colocalization). Here we describe an open source plugin for ImageJ called EzColocalization to visualize and measure colocalization in microscopy images. EzColocalization is designed to be easy to use and customize for researchers with minimal experience in quantitative microscopy and computer programming. Features of EzColocalization include: (i) tools to select individual cells and organisms from images; (ii) filters to select specific types of cells and organisms based on physical parameters and signal intensity; (iii) heat maps and scatterplots to visualize the localization patterns of reporters; (iv) multiple metrics to measure colocalization for two or three reporters; (v) metric matrices to systematically measure colocalization at multiple combinations of signal intensity thresholds; and (vi) data tables that provide detailed information on each cell in a sample. These features make EzColocalization well-suited for experiments with low reporter signal, complex patterns of localization, and heterogeneous populations of cells and organisms.
机译:通常可以通过确定它们定位于哪些细胞结构和其他分子(即共定位)来获得对生物分子的功能和调节的了解。在这里,我们描述了ImageJ的开源插件,称为EzColocalization,用于可视化和测量显微图像中的共定位。 EzColocalization的设计易于使用,并为定量显微镜和计算机编程方面的最少经验的研究人员定制。 EzColocalization的功能包括:(i)从图像中选择单个细胞和生物的工具; (ii)过滤器根据物理参数和信号强度选择特定类型的细胞和生物; (iii)热图和散点图,以可视化报告者的定位模式; (iv)多个指标来衡量两个或三个报告者的共定位; (v)用于在信号强度阈值的多个组合下系统地测量共定位的度量矩阵; (vi)数据表,提供有关样本中每个单元格的详细信息。这些功能使EzColocalization非常适合用于低报道基因信号,复杂的定位模式以及细胞和生物体的异质种群的实验。

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