bioRxiv · 10.1101/2020.05.28.120527
Agile workflow for interactive analysis of mass cytometry data
Abstract
MotivationSingle-cell proteomics technologies, such as mass cytometry, have enabled characterization of cell-to-cell variation and cell populations at a single cell resolution. These large amounts of data, however, require dedicated, interactive tools for translating the data into knowledge. ResultsWe present a comprehensive, interactive method called Cyto to streamline analysis of large-scale cytometry data. Cyto is a workflow-based open-source solution that automatizes the use of of state-of-the-art single-cell analysis methods with interactive visualization. We show the utility of Cyto by applying it to mass cytometry data from peripheral blood and high-grade serous ovarian cancer (HGSOC) samples. Our results show that Cyto is able to reliably capture the immune cell sub-populations from peripheral blood as well as cellular compositions of unique immune- and cancer cell subpopulations in HGSOC tumor and ascites samples. AvailabilityThe method is available as a Docker container at https://hub.docker.com/r/anduril/cyto and the user guide and source code are available at https://bitbucket.org/anduril-dev/cyto Contactsampsa.hautaniemi@helsinki.fi Supplementary informationSupplementary material is available and FCS files are hosted at flowrepository.org/id/FR-FCM-Z2LW
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Casado, J., Lehtonen, O., Rantanen, V., Kaipio, K., Pasquini, L., Häkkinen, A., Petrucci, E., Carpen, O., Biffoni, M., Farkkila, A., Hautaniemi, S.. 2020-05-30. Agile workflow for interactive analysis of mass cytometry data. https://doi.org/10.1101/2020.05.28.120527
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