Quantitative colocalization analysis is an advanced digital imaging tool to examine antigens of interest in immunofluorescence images obtained using confocal microscopes. It employs specialized algorithms to estimate the degree of overlap of fluorescence signals and thus enables acquiring important new information not otherwise obtainable using qualitative approaches alone. As raw confocal images have high levels of background, they should be prepared to become suitable for reliable calculation of colocalization coefficients by correcting it. We provide concise theoretical basis of quantitative colocalization analysis, discuss its limitations, and describe proper use of the technique. The use of quantitative colocalization analysis is demonstrated by studying bile salt export pump and multidrug resistance associated protein 2 in the liver and major basic protein and platelet activating factor receptor antigens in conjunctiva. The review is focused on the applicability and correct interpretation of the results of colocalization coefficients calculations.

Colocalization is an important finding in many cell biological studies. This unit describes a protocol for quantitative evaluation of images with colocalization based on the calculation of a number of specialized coefficients. First, images of double‐stained sections are subjected to background correction. Then, various coefficients are calculated. Meanings of the coefficients and a guide to interpretation of their results indicating either presence or absence of colocalization are given. Success in colocalization studies depends on the quality of analyzed images, proper preparation of them for coefficients calculations, and correct interpretation of obtained results. This protocol helps to ensure reliability of colocalization coefficients calculations. Curr. Protoc. Cell Biol. 39:4.19.1‐4.19.16. © 2008 by John Wiley & Sons, Inc.

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Quantitative colocalization studies suffer from the lack of unified approach to interpret obtained results. We developed a tool to characterize the results of colocalization experiments in a way so that they are understandable and comparable both qualitatively and quantitatively. Employing a fuzzy system model and computer simulation, we produced a set of just five linguistic variables tied to the values of popular colocalization coefficients: “Very Weak”, “Weak”, “Moderate”, “Strong”, and “Very Strong”. The use of the variables ensures that the results of colocalization studies are properly reported, easily shared, and universally understood by all researchers working in the field. When new coefficients are introduced, their values can be readily fitted into the set.

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