The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
COMPASS identifies T-cell subsets correlated with clinical outcomes
Open accessAbstract
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.
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Vaccination with ALVAC and AIDSVAX to Prevent HIV-1 Infection in Thailand
Rerks-Ngarm, S., Pitisuttithum, P., Nitayaphan, S., Kaewkungwal, J., Chiu, J., Paris, R., Premsri, N., Namwat, C., de Souza, M., Adams, E., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0908492 · Cited by 3,034
Self-citationImmune-Correlates Analysis of an HIV-1 Vaccine Efficacy Trial
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Self-citationMultifunctional TH1 cells define a correlate of vaccine-mediated protection against Leishmania major
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Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection
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SPICE: Exploration and analysis of post‐cytometric complex multivariate datasets
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Critical assessment of automated flow cytometry data analysis techniques
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Self-citationBayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
Scott, J. G., & Berger, J. O. (2010) · The Annals of Statistics · doi:10.1214/10-aos792 · Cited by 573
Detecting differential gene expression with a semiparametric hierarchical mixture method
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Self-citationProtective CD8+ T-cell immunity to human malaria induced by chimpanzee adenovirus-MVA immunisation
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Cited by
Alberer, M., Gnad-Vogt, U., Hong, H. S., Mehr, K. T., Backert, L., Finak, G., Gottardo, R., Bica, M. A., Garofano, A., Koch, S. D., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)31665-3 · Cited by 530
Self-citationPark, L. M., Lannigan, J., & Jaimes, M. C. (2020) · Cytometry Part A · doi:10.1002/cyto.a.24213 · Cited by 350
Cytotoxic CD4 T Cells—Friend or Foe during Viral Infection?
Juno, J. A., van Bockel, D., Kent, S. J., Kelleher, A. D., Zaunders, J. J., & Munier, C. M. L. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.00019 · Cited by 195
Persistent cellular immunity to SARS-CoV-2 infection
Breton, G., Mendoza, P., Hägglöf, T., Oliveira, T. Y., Schaefer-Babajew, D., Gaebler, C., Turroja, M., Hurley, A., Caskey, M., & Nussenzweig, M. C. (2021) · Journal of Experimental Medicine · doi:10.1084/jem.20202515 · Cited by 129
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Metadata
- Authors
- Lin, L., Finak, G., Ushey, K., Seshadri, C., Hawn, T. R., Frahm, N., Scriba, T. J., Mahomed, H., Hanekom, W., Bart, P.-A., Pantaleo, G., Tomaras, G. D., Rerks-Ngarm, S., Kaewkungwal, J., Nitayaphan, S., Pitisuttithum, P., Michael, N. L., Kim, J. H., Robb, M. L., O'Connell, R. J., Karasavvas, N., Gilbert, P., C De Rosa, S., McElrath, M. J., & Gottardo, R.
- Venue
- Nature Biotechnology
- Published
- 2015-05-25
- Volume
- 33
- Issue
- 6
- Pages
- 610-616
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W1607536760
- Cited by
- 278
- References
- 27
- FWCI
- 10.31
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Lin, L., Finak, G., Ushey, K., Seshadri, C., Hawn, T. R., Frahm, N., Scriba, T. J., Mahomed, H., Hanekom, W., Bart, P.-A., Pantaleo, G., Tomaras, G. D., Rerks-Ngarm, S., Kaewkungwal, J., Nitayaphan, S., Pitisuttithum, P., Michael, N. L., Kim, J. H., Robb, M. L., . . . Gottardo, R. (2015). COMPASS identifies T-cell subsets correlated with clinical outcomes. Nature Biotechnology. https://doi.org/10.1038/nbt.3187
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