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Title: COMPASS identifies T-cell subsets correlated with clinical outcomes
Authors: Lin Lin
Greg Finak
Kevin Ushey
Chetan Seshadri
Thomas R. Hawn
Nicole Frahm
Thomas J. Scriba
Hassan Mahomed
Willem Hanekom
Pierre Alexandre Bart
Giuseppe Pantaleo
Georgia D. Tomaras
Supachai Rerks-Ngarm
Jaranit Kaewkungwal
Sorachai Nitayaphan
Punnee Pitisuttithum
Nelson L. Michael
Jerome H. Kim
Merlin L. Robb
Robert J. O'Connell
Nicos Karasavvas
Peter Gilbert
Stephen C. De Rosa
M. Juliana McElrath
Raphael Gottardo
Fred Hutchinson Cancer Research Center
University of Washington, Seattle
South African Tuberculosis Vaccine Initiative
Centre Hospitalier Universitaire Vaudois
Duke University Medical Center
Thailand Ministry of Public Health
Mahidol University
Armed Forces Research Institute of Medical Sciences, Thailand
Walter Reed Army Institute of Research
Keywords: Biochemistry, Genetics and Molecular Biology;Chemical Engineering;Engineering;Immunology and Microbiology
Issue Date: 11-Jun-2015
Citation: Nature Biotechnology. Vol.33, No.6 (2015), 610-616
Abstract: © 2015 Nature America, Inc. All rights reserved. Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software.
ISSN: 15461696
Appears in Collections:Scopus 2011-2015

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