The ultrastructural localization of various antigens in a cell using antibodies conjugated to gold particles is a powerful instrument in biological research. However, statistical or stereological tools for testing the observed patterns for significant clustering or colocalization are missing. The paper presents a method for the quantitative analysis of single or multiple immunogold labeling patterns using interpoint distances and tests the method using experimental data, The clustering or colocalization of gold particles was detected using various characteristics of the distribution of distances between them. Pair correlation and cross-correlation functions were used for exploratory analysis; second order reduced K (or cross-K) functions were used for testing the statistical significance of observed events. Confidence intervals of function values were estimated by Monte Carlo simulations of the Poisson process for independent particles, and results were visualized in histograms. Furthermore, a suitability of K functions modified by censoring or weighting was tested. The reliability of the method was assessed by evaluating the labeling patterns of nascent DNA and several nuclear proteins with known functions in replication foci of HeLa cells. The results demonstrate that the method is a powerful tool in biological investigations for testing the statistical significance of observed clustering or colocalization patterns in immunogold labeling experiments.