Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA.
Atomwise Inc., San Francisco, CA, USA.
Sci Rep. 2018 Oct 25;8(1):15764. doi: 10.1038/s41598-018-33592-8.
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.
通过确定生物分子与哪些细胞结构和其他分子相互作用（即共定位），可以深入了解其功能和调控机制。本文描述了一个名为 EzColocalization 的 ImageJ 开源插件，用于可视化和测量显微镜图像中的共定位。EzColocalization 的设计目的是让具有最少定量显微镜和计算机编程经验的研究人员易于使用和自定义。EzColocalization 的功能包括：（i）从图像中选择单个细胞和生物体的工具；（ii）根据物理参数和信号强度选择特定类型的细胞和生物体的滤波器；（iii）热图和散点图可视化报告者的定位模式；（iv）用于测量两个或三个报告者共定位的多种指标；（v）用于在多个信号强度阈值组合下系统地测量共定位的指标矩阵；以及（vi）数据表，提供样本中每个细胞的详细信息。这些功能使 EzColocalization 非常适合具有低报告者信号、复杂定位模式和异质细胞和生物体群体的实验。
