As image colocalization analysis is involved in the majority of methods, the related coefficients are reported. Fluorescent microscopy (FM) is the universal approach utilized in every technique, thus we discuss several FM variants. Simple Summary: We comparatively discuss all possible methodologies for the complex DNA damage in situ detection. Our results give a first extensive characterization of the quality control procedures of a light microscope, with an automated data processing and experimental limit values that can be used by core facility staff and researchers to monitor the microscope performance over time. After processing and comparing the data of microscopes from more than ten imaging facilities, we test the robustness of the metrics and the protocols by determining experimental limit values. We designed an ImageJ/FiJi java plugin named MetroloJ_QC to incorporate the identified metrics and automatize the data processing for the analysis. Seven protocols specify metrics on measuring the lateral and axial resolution (Point-Spread Function) of the system, field flatness, chromatic aberrations and co-registration, illumination power monitoring and stability, stage drift and positioning repeatability and finally temporal and spatial noise sources of camera detectors. In this paper, we test the acquisition protocols on the mainly used microscope techniques (wide-field, spinning disk and confocal microscopy) with simple quality control tools. Three levels of microscope quality control procedures should be considered: i) usage of accessible and affordable tools and samples, ii) execution of easy and fast, preferably automatized, acquisition protocols, iii) analysis of data in the most automated way possible with adequate metrics for long-term monitoring. To achieve that level of confidence, monitoring the stability of the microscope performance over time with standardized quality testing routines is essential for mining quantitative data. Reliable, reproducible and comparable results are what biology requires from microscopy.
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The software for conditional colocalization analysis is available at. We benchmark the approach and showcase its application to investigate receptor-downstream adaptor colocalization relationships in the context of functionally relevant plasma membrane locations.
Going beyond the question of whether colocalization is present or not, it addresses the question of whether the colocalization between two entities is influenced, positively or negatively, by their colocalization with a third entity. Here, we describe an approach, termed “conditional colocalization analysis,” for analyzing the colocalization relationships between three molecular entities in three-color microscopy images. However, almost all colocalization analyses are designed for two-color images, limiting the type of information that they reveal. It provides information on the localization of molecules within subcellular compartments and allows the interrogation of known molecular interactions in their cellular context. Colocalization analysis of multicolor microscopy images is a cornerstone approach in cell biology.
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