Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients
We profiled scRNA-seq of 284 samples collected from 196 individuals, including 22 patients with mild/moderate symptoms, 54 hospitalized patients with severe symptoms, and 95 recovered convalescent persons, as well as 25 healthy controls. The samples were obtained from various tissue types, including human peripheral blood mononuclear cells (249), bronchoalveolar lavage fluid (12) and pleural pleural effusion (1)/sputum (22).
Provenance — who produced it, who reused it
Linked to 12 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- Context-aware deconvolution of cell–cell communication with Tens... 2022 · 109 cites
- Integrating single-cell RNA and T cell/B cell receptor sequencin... 2025 · 90 cites
- Integrating single-cell sequencing data with GWAS summary statis... 2022 · 73 cites
9 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.