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@MISC{Georg:169094,
      author       = {Georg, Philipp and Astaburuaga-García, Rosario and
                      Bonaguro, Lorenzo and Blüthgen, Nils and Sawitzki, Birgit},
      title        = {{D}ataset: {C}omplement activation induces excessive {T}
                      cell cytotoxicity in severe {COVID}-19: {A}nalysis of single
                      cell data cohort 1 ({B}erlin), v1.0.0},
      publisher    = {Zenodo},
      reportid     = {DZNE-2022-01801},
      year         = {2021},
      abstract     = {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: The raw data can be
                      found in
                      https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE175450
                      Other files to reproduce the analysis
                      $(scRNAseq_analysis_1preprocessing.Rmd,$
                      $scRNAseq_analysis_2clustering.Rmd,$
                      $scRNAseq_analysis_3convalescent.Rmd):$
                      $scRNAseq_Sawitzki_RECAST_09_2021.xlsx$ : Metadata
                      $scRNAseq_genelist_annotation.xlsx$ : G ene list for the
                      annotation of T cells (Also in Mendeley, see Data and Code
                      Availability).
                      $scRNAseq_GO_RESPONSE_TO_TYPE_I_INTERFERON.txt$ ,
                      $scRNAseq_GO_DEFENSE_RESPONSE_TO_VIRUS.txt$ , ,
                      $scRNAseq_GO_T_CELL_MEDIATED_CYTOTOXICITY.txt$ : Gene lists
                      for the signatures “Response to Type I Interferon” ,
                      “Defense Response to virus” and “Cytotoxicity” used
                      for GSEA. (Also in Table S2). $scRNAseq_traj18_trav10.txt$ ,
                      $scRNAseq_trbv25.txt$ : sequences to determine the
                      proportion of TRAV10-TRAJ18-TRBV25 pairing T cell clones
                      across all T cell clusters.},
      keywords     = {COVID-19 (Other) / single cell analysis (Other) /
                      clustering (Other) / CyTOF (Other) / scRNA-seq (Other)},
      cin          = {AG Schultze},
      cid          = {I:(DE-2719)1013038},
      pnm          = {354 - Disease Prevention and Healthy Aging (POF4-354)},
      pid          = {G:(DE-HGF)POF4-354},
      typ          = {PUB:(DE-HGF)32},
      doi          = {10.5281/zenodo.5771936},
      url          = {https://pub.dzne.de/record/169094},
}