Sarah Adamo
Jan Michler
Yves Zurbuchen
Carlo Cervia
Patrick Taeschler
Miro E. Raeber
Simona Baghai Sain
Jakob Nilsson
Andreas E. Moor
Onur Boyman
2021-12-09
<p>The datasets uploaded in this Zenodo entry were generated in the single cell RNA sequencing part of the project.</p>
<p>For the scRNAseq analysis, cells from ten patients and the same time point were pooled together, generating four individual sample sets in total: (1) patients CoV2_T001- CoV2_T010, acute; (2) patients CoV2_T001- CoV2_T010, six months post-infection; (3) patients CoV2_T011- CoV2_T020, acute; (4) patients CoV2_T011- CoV2_T011-20, six months post-infection.</p>
<p>We additionally generated two more sample sets: using 5000 unsorted PBMCs from each patient’s sample: (5) patients CoV2_T001- CoV2_T010, six months post-infection unsorted; (6) patients CoV2_T011- CoV2_T020, six months post-infection unsorted. Finally, using PBMCs from four healthy donors, we generated sample set (7) by sorting and pooling 2000 CD8+ T cells from each healthy donor sample.</p>
<p>We are here providing the pre-processed sets for each sample set (1-7), i.e. :<br>
- "filtered feature bc matrix" files, as output from the ‘cellranger multi’ pipeline (Cell Ranger version 5.0.0), containing cell-RNA count matrices and cell-ADT matrices. ADTs comprise counts for TotalSeq antibodies and dCODE Dextramers.<br>
- "filtered_contig_annotations.csv" files, as output from the ‘cellranger multi’ pipeline (Cell Ranger version 5.0.0), containing High-level annotations of each high-confidence, cellular contig for TCR clonal analysis. This file is not present for sets 5 and 6, because we did not perform TCR profiling for these samples.<br>
- "clusters.tsv" files, as output from the souporcell SNP analysis (version 2). To cluster cells based on their patient specific genetic variants, we merged sample sets 1, 2 and 5 (comprising sorted cells from both time points of patients CoV2_T001- CoV2_T010 and unsorted cells of the same patients) and sets 3, 4 and 6 (comprising cells from both time points of patients CoV2_T011- CoV2_T020 and unsorted cells of the same patients). Then, we executed the souporcell pipeline with option <em>k=10 </em>(number of clusters to be determined) for each of the two merged sample sets.</p>
<p>Together, these files allow to reproduce the analysis as reported in the paper.</p>
<p>Additionally, we provide the Seurat Objects "Integrated.h5seurat" and "Integrated_NA_filtered.h5seurat" which can be used to skip the pre-processing steps of the data analysis. See the code provided on https://github.com/Moors-Code/SARS-CoV-2-Tcell-Boyman-collaboration for details.</p>
<p> </p>
https://doi.org/10.5281/zenodo.5770747
oai:zenodo.org:5770747
Zenodo
https://doi.org/10.5281/zenodo.5119632
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Signature of long-lived memory CD8+ T cells in acute SARS-CoV-2 infection
info:eu-repo/semantics/other