Abstract Cell communication is predominantly governed by secreted proteins, whose diverse secretion patterns often signify underlying physiological irregularities. Unraveling the intricacies of these secreted signals at the single-cell level is crucial for a comprehensive understanding of regulatory mechanisms involving various molecular agents. To elucidate the array of cell secretion signals, encompassing both anisotropic and isotropic biomolecular cues from individual immune cells or disparate cell types, we introduce the Secretion Signal Map (S2Map). S2Map is an innovative online interactive analytical platform that incorporates qualitative metrics, the signal inequality index (SII) and the signal coverage index (SCI), which are exquisitely sensitive in facilitating the measurement of dissymmetry and diffusion of cumulative signals and signal dynamics in temporal analysis. S2Map's innovation lies in its depiction of signals through real-time secretion hotspots, and cumulative secretion contour lines, complemented by the visualization of potential cell secretion signal velocities via stream plots generated by regression models. We evaluated the SII and SCI performance in distinguishing the simulated signal diffusion model. Presently, S2Map hosts a repository of 12 datasets that map single-cell and two-cell secretion dynamics. These datasets serve as a resource to explore secretion signal types. We anticipate that S2Map will be a powerful approach to delve into the complexities of physiological systems, providing insights into the regulation of protein production, such as cytokines at the remarkable resolution of single cells. The S2Map server is publicly accessible via https://au-s2map.streamlit.app/. Citation Format: Zongliang Yue, Lang Zhou, Fengyuan Huang, Pengyu Chen. S2Map: An online interactive analytical platform for quantitative signal measurement of cell Secretion Signal Map [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7428.