Rapid advances in flow cytometry and other single-cell technologies have enabled high-dimensional, multi-parameter, high-throughput measurements of individual cells. Numerous questions about cell population heterogeneity can now be addressed, as these novel technologies permit single-cell analysis of antigen-specific T-cells. Unfortunately, there is a lack of computational tools to take full advantage of these complex data. COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject