The IgE receptor signaling system in mast cells is widely studied for its role in the allergic response, and as a model system for immune receptor signaling. In the present studies, we focus on the earliest events in the signaling cascade, in which antigen cross-links IgE receptors (IgE-FcεRI), forming clusters, which couple to the tyrosine kinase Lyn, a cytoplasmic protein anchored by fatty acyl chains to the inner leaflet of the plasma membrane. Biochemical techniques have suggested that the coupling between Lyn and FcεRI is mediated by membrane lipids. Modern microscopy and computational methods enable a more detailed study of these cell signaling processes at the nanoscale, allowing us to investigate the specific molecular events that are required for cell stimulation. We use super-resolution fluorescence microscopy (PALM/STORM) to quantify the redistribution of IgE-FcεRI upon simulation with antigen. Using structurally defined trivalent ligands, built on rigid dsDNA scaffolds, we generate IgE-FcεRI clusters of a well-defined spatial configuration. We use PALM/STORM to quantitatively measure the size and density of clusters, and two-color PALM/STORM to measure the colocalization of Lyn and other membrane components with the clusters. We show that IgE-FcεRI clusters with a higher receptor density are more effective at recruiting Lyn, and stimulating downstream signaling events. Though the change in Lyn concentration is small, it leads to cellular degranulation and other major functional consequences. In addition to the well-known mast cell responses, we describe a novel mechanism by which the activity of Lyn leads to an increase in IgE-FcεRI clustering, providing positive feedback on the signal initiation process. We find lipid reorganization due to IgE-FcεRI clustering to be too subtle to detect in our PALM/STORM system, but using computational modeling in conjunction with previous work, we gain new insight to the role that lipids might play. Using the Ising model, we compute the binding energy for recruitment of a kinase into a receptor cluster, assuming that both proteins partition into the same membrane phase. We extend this model into a full phase diagram for membranes, computed using machine learning techniques, and examine how kinase binding energy depends on the phase state of the membrane. We predict a modest binding energy for membranes that exist as a microemulsion or near a critical phase transition, and a much larger binding energy if the membrane exists near a tricritical point. Taken together, our results provide new, molecular-level insight about protein-mediated and lipid-mediated processes that contribute to the initiation of IgE-FcεRI signaling.