![]() ![]() The protocol consists of three core computational stages: (1) data import and quality control (2) dimensionality reduction and unsupervised clustering and (3) annotation and differential testing, all contained within an R-based open-source framework. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users’ needs. Here, we describe ImmunoCluster ( ), an R package for immune profiling cellular heterogeneity in high-dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a nonspecialist. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, and it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. Francis Crick Institute, United Kingdom.Cancer Systems Biology Laboratory, The Francis Crick Institute, United Kingdom.Haematology Department, Guy’s Hospital, United Kingdom.Centre for Host Microbiome Interaction, FoDOCS, King’s College, Guy’s Hospital, United Kingdom.UCL Cancer Institute, Paul O'Gorman Building, University College London, United Kingdom.Institut Cochin, Institut National de la Santé et de la Recherche Médicale U1016, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 8104, Université Paris Descartes, France.School of Cancer and Pharmaceutical Sciences, King’s College London, Faculty of Life Sciences and Medicine, Guy’s Hospital, United Kingdom. ![]()
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