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COMPASS identifies T-cell subsets correlated with clinical outcomes

Lin, L., Finak, G., Ushey, K. et al.

Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells and allowed interrogation of cell population heterogeneity. Computational tools to take full advantage of these technologies are lacking. Here, we present COMPASS, a computational framework for unbiased polyfunctionality analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed functional cell subsets and select those most likely to exhibit antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, while subject-level responses are quantified by two novel summary statistics that can be correlated directly with clinical outcome, and describe the quality of an individual’s (poly)functional response. Using three clinical datasets of cytokine production we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals novel cellular correlates of protection in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software.

Citation

Lin, L., Finak, G., Ushey, K. et al. "COMPASS identifies T-cell subsets correlated with clinical outcomes" Nature Biotechnology (2015): 610–6