Flow cytometry data (2) from: Proteomic analysis of circulating immune cells identifies cellular phenotypes associated with COVID-19 severity, Potts et al.

Published: 10 May 2023| Version 1 | DOI: 10.17632/jv9jvm3r98.1
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Description

Full associated publication: 'Proteomic analysis of circulating immune cells identifies cellular phenotypes associated with COVID-19 severity', Potts et al (2023). Raw 18-colour flow cytometry data characterising PBMC derived from cohort of 36 donors, including healthy controls and individuals infected with SARS-CoV-2. Data were utilised to validate upregulation of the markers CEACAM1, CEACAM6, CEACAM8, CD177, CD63 and CD89 in severe COVID-19 and phenotype immune cell populations upregulating these markers. Flow cytometry data were collected over 3 seaparate experiments on a Cytek Aurora spectral flow cytometer and are provided as unmixed and unprocessed .fcs files from the second experiment. These data can be analysed using the widely used FlowJo analysis software. Each data file is titled with indicators for the donor ID (CVXXXX) and whether the sample was stained with the antibody cocktail or left as an unstained control. Full metadata for each donor can be found in the associated publication.

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Institutions

Cambridge Institute for Medical Research, University of Cambridge

Categories

Immunology, Clinical Virology, Severe Acute Respiratory Syndrome Coronavirus 2, COVID-19

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