Published December 10, 2021 | Version Version 1.0.0
Dataset Open

Complement activation induces excessive T cell cytotoxicity in severe COVID-19: Analysis of single cell data cohort 1 (Berlin).

  • 1. (1) Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 13353 Berlin, Germany
  • 2. (2) Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany. (3) IRI Life Sciences, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
  • 3. (4) Genomics and Immunoregulation, Life and Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany, (5) Systems Medicine, Deutsches Zentrum für Neurodegenerativen Erkrankungen (DZNE), 53127 Bonn, Germany
  • 4. (6) Institute of Medical Immunology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 13353 Berlin, Germany, (7) Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany

Description

This repository contains the R Markdown files with the analysis of CyTOF and scRNA-seq data corresponding to cohort 1 (Berlin) analysed in Georg et al. 2021 "Complement activation induces excessive T cell cytotoxicity in severe COVID-19". Additionally, here we include the necessary CyTOF data to reproduce this analysis.

CyTOF data:

  • The debarcoded fcs files (before batch-correction) can be found in https://flowrepository.org/id/FR-FCM-Z4P5. \
  • Here you can find the necessary data to reproduce the analysis (cytof_analysis.Rmd, cytof_analysis.html):
    • data_norm_all.csv: single-cell protein expression data (after batch-normalization and in linear scale).
    • data_Tcells_annotated.csv: single-cell protein expression of gated T cells with cluster annotation.
    • phenograph_CD4_k30.csv, phenograph_CD8_k30.csv, phenograph_TCRgd_k30.csv: output from Louvain Clustering computed with PhenoGraph (https://github.com/jacoblevine/PhenoGraph) per T cell compartment.
    • clusterannotation.csv: annotation for each cluster and metacluster

scRNA-seq data:

Files

scRNAseq_GO_DEFENSE_RESPONSE_TO_VIRUS.txt

Files (6.2 GB)

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