A versatile toolbox for semi-automatic cell-by-cell object-based colocalization analysis.

ABSTRACT: Differential fluorescence labeling and multi-fluorescence imaging followed by colocalization analysis is commonly used to investigate cellular heterogeneity in situ. This is particularly important when investigating the biology of tissues with diverse cell types. Object-based colocalization analysis (OBCA) tools can employ automatic approaches, which are sensitive to errors in cell segmentation, or manual approaches, which can be impractical and tedious. Here, we present a novel set of tools for OBCA using a semi-automatic approach, consisting of two ImageJ plugins, a Microsoft Excel macro, and a MATLAB script. One ImageJ plugin enables customizable processing of multichannel 3D images for enhanced visualization of features relevant to OBCA, and another enables semi-automatic colocalizatio

SUBMITTER: Lunde A 

PROVIDER: S-EPMC7643144 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature