Agile Workflow For Interactive Analysis Of Mass Cytometry Data
Casado J; Rantanen V; Lehtonen O; Carpén O; Petrucci E; Biffoni M; Häkkinen A; Hynninen J; Färkkilä A; Kaipio K; Hietanen S; Hautaniemi S; Pasquini L
https://urn.fi/URN:NBN:fi-fe2021042822145
Tiivistelmä
Motivation: Single-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, require dedicated, interactive tools for translating the data into knowledge.
Results: We present a comprehensive, interactive method called Cyto to streamline analysis of large-scale cytometry data. Cyto is a workflow-based open-source solution that automates the use 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.
Availability: The 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.
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