title: Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.
abstract: An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Lin
authors.initials: L
authors.lastname: Lin
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Jacob
authors.initials: J
authors.lastname: Frelinger
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Wenxin
authors.initials: W
authors.lastname: Jiang
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Greg
authors.initials: G
authors.lastname: Finak
authors.affiliation: Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington.
authors.forename: Chetan
authors.initials: C
authors.lastname: Seshadri
authors.affiliation: Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
authors.forename: Pierre-Alexandre
authors.initials: PA
authors.lastname: Bart
authors.affiliation: Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Pantaleo
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Julie
authors.initials: J
authors.lastname: McElrath
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Steve
authors.initials: S
authors.lastname: DeRosa
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
authors.forename: Raphael
authors.initials: R
authors.lastname: Gottardo
mesh_terms: D000293:Adolescent; D000465:Algorithms; D000941:Antigens / Q000276:immunology*; D019295:Computational Biology / Q000379:methods; D016207:Cytokines / Q000032:analysis*; D000939:Epitopes / Q000276:immunology*; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D007963:Leukocytes, Mononuclear; D013194:Staining and Labeling; D013601:T-Lymphocytes / Q000145:classification / Q000276:immunology*
chemical_list: D000941:Antigens; D016207:Cytokines; D000939:Epitopes
keywords: antigen-specific T cells; automated gating; dimension reduction; intracellular cytokine staining; polyfunctionality; visualization