Hye-Rim Shin

In the nucleus, distinct, discrete spots or regions called “foci” have been identified, each harboring a specific molecular function. Accurate and efficient quantification of these foci is essential for understanding cellular dynamics and signaling pathways. In this study, we present an innovative automated image analysis method designed to precisely quantify subcellular foci within the cell nucleus. Manual foci counting methods can be tedious and time-consuming. To address these challenges, we developed an open-source software that automatically counts the number of foci from the indicated image files. We compared the foci counting efficiency, velocity, accuracy, and convenience of Foci-Xpress with those of other conventional methods in foci-induced models. We can adjust the brightness of foci to establish a threshold. The Foci-Xpress method was significantly faster than other conventional methods. Its accuracy was similar to that of conventional methods. The most significant strength of Foci-Xpress is automation, which eliminates the need for analyzing equipment while counting. This enhanced throughput facilitates comprehensive statistical analyses and supports robust conclusions from experiments. Furthermore, automation completely rules out biases caused by researchers, such as manual errors or daily variations. Thus, Foci-Xpress is a convincing, convenient, and easily accessible focus-counting tool for cell biologists.