28 research outputs found

    Cyclone: an accessible pipeline to analyze, evaluate, and optimize multiparametric cytometry data

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    In the past decade, high-dimensional single-cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation, which are computationally intense and difficult to evaluate and optimize. Here, we present Cytometry Clustering Optimization and Evaluation (Cyclone), an analysis pipeline integrating dimensionality reduction, clustering, evaluation, and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full-spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification but also enables the unsupervised identification of lymphocytes and mononuclear phagocyte subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on a variety of cytometry datasets, which will further power immunology research and provide a scaffold for biological discovery

    ratioNext Scores

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    Final 'ratioNext' scores of xCell signatures, as shown in Fig.2B and elsewher

    xCell signature gene sets

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    Lists of genes used for each of the 64 cell type signatures used by xCel

    Signature-Cell Type Target Map

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    Targeting relationship between xCell cell type signatures and cell types identified in healthy human endometrium scRNAseq dataset, used in Fig.2

    Color Palette

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    Color palette used for immune subtypes in Fig.3A, and violin plots in 3C, 5C, 5D, S7

    Normalized signature scores of xCell signatures

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    Medium normalized signature score between each xCell cell type signature and each cell type identified in healthy human endometrium scRNAseq dataset, as shown in Fig.2
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