Agile workflow for interactive analysis of mass cytometry data
Casado, J., Lehtonen, O., Rantanen, V.
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.
Casado, J., Lehtonen, O., Rantanen, V. "Agile workflow for interactive analysis of mass cytometry data" Bioinformatics (2020): DOI: 10.1093/bioinformatics/btaa946