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00925njm 22002777a 4500 dc Jimenez-Carretero, Daniel author Ligos, José M author Martínez-López, María author Sancho, David author Montoya, María C author 2018 Advances in flow cytometry (FCM) increasingly demand adoption of computational analysis tools to tackle the ever-growing data dimensionality. In this study, we tested different data input modes to evaluate how cytometry acquisition configuration and data compensation procedures affect the performance of unsupervised phenotyping tools. An analysis workflow was set up and tested for the detection of changes in reference bead subsets and in a rare subpopulation of murine lymph node CD103+ dendritic cells acquired by conventional or spectral cytometry. Raw spectral data or pseudospectral data acquired with the full set of available detectors by conventional cytometry consistently outperformed datasets acquired and compensated according to FCM standards. Our results thus challenge the paradigm of one-fluorochrome/one-parameter acquisition in FCM for unsupervised cluster-based analysis. Instead, we propose to configure instrument acquisition to use all available fluorescence detectors and to avoid integration and compensation procedures, thereby using raw spectral or pseudospectral data for improved automated phenotypic analysis. J Immunol . 2018 May 15;200(10):3319-3331 10.4049/jimmunol.1800446 1550-6606 Journal of immunology (Baltimore, Md. : 1950) 29735643 http://hdl.handle.net/20.500.12105/15162 Flow Cytometry Data Preparation Guidelines for Improved Automated Phenotypic Analysis.