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Chunk #20 — Results — scCODA detects cell-type changes in COVID-19 patients that were not detected with non-compositional tests but confirmed in larger-scale studies

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scCODA is a Bayesian model for compositional single-cell data analysis.
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between moderate vs severe cases, as well as a credible increase of neutrophils in healthy and moderate vs severe at an FDR level of 0.2 using Plasma as reference. For comparison, ANCOM identified significant changes in mDCs between healthy and moderate, as well as neutrophils between healthy and moderate vs severe at alpha=0.2, respectively. The correlation of T-cell abundances with severity is well established and has been used as risk factors for severe cases22,23. A decrease of NK cells with COVID-19 severity was observed between recovered and diseased patients23 in PBMC through FACS analysis. Finally, higher neutrophil proportions have been associated with severe outcomes24 and are suspected to be the main drivers of the exacerbated host response25, further confirming scCODA’s findings.