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Martin Wasser, Joo Guan Yeo, Pavanish Kumar, Thaschawee Arkachaisri,Su Li Poh, Jing Yao Leong, Kee Thai Yeo, Salvatore Albani (Translational Immunology Institute, SingHealth DukeNUS Academic Medical Centre, Singapore)
Mass cytometry (CyTOF) is a high-dimensional single-cell technology where a single experiment can provide a holistic view of the immune system in multiple samples. Motivated by the idea that a better understanding of healthy human immunome development may provide novel insights into disease mechanisms, we applied CyTOF to quantify the expression of 63 proteins in nearly 200 peripheral blood samples of healthy donors from birth to old age. To build the EPIC (Extended Poly-dimensional Immunome characterisation) immune atlas, we developed a computational pipeline that integrates protein expression data with clinical metadata and phenotypic information inferred from clustering and assisted cell-type annotation. To visualise the high-dimensional immune atlas data, we built the R shiny app SciAtlasMiner (Single-cell immune atlas miner), which can run on standalone PCs and web-servers. Users can explore the developing human immune landscape using diverse interactive, highly customisable visualisations at different resolution levels. Besides examining data from our lab, users can also upload their own CyTOF data and obtain instant frequency estimates of annotated cell populations. Data min