Single-cell multi-omics analysis of the immune response in COVID-19

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Cell Metadata

regulatory T cell

Ontology Term: regulatory T cellCL:0000815
SynonymsTerms that have the same, or nearly the same, meaning as the selected cell type.: suppressor T cell, regulatory T-lymphocyte, regulatory T-cell, suppressor T-lymphocyte, regulatory T lymphocyte, Treg, suppressor T-cell, suppressor T lymphocyte
CategoryClass of which the cell type is a subclass.: mature T cellCL:0002419
Marker Gene EvidenceGene markers used by researcher to assign this cell annotation.: CD3G, CCR7, CD27, CD4, IKZF2, FOXP3, CTLA4, CXCR5, TOX
Canonical Marker Genes: unknown
Rationale: NA

Set of Labels Description: Single-cell transcriptome analysis of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19
Annotation Method: both
Algorithm Name: Azimuth
Algorithm Version: v1
Algorithm URL: https://azimuth.hubmapconsortium.org/

Ontology Term: regulatory T cellCL:0000815
SynonymsTerms that have the same, or nearly the same, meaning as the selected cell type.: suppressor T cell, regulatory T-lymphocyte, regulatory T-cell, suppressor T-lymphocyte, regulatory T lymphocyte, Treg, suppressor T-cell, suppressor T lymphocyte
CategoryClass of which the cell type is a subclass.: mature T cellCL:0002419
Marker Gene EvidenceGene markers used by researcher to assign this cell annotation.: CD3G, CCR7, CD27, CD4, IKZF2, FOXP3, CTLA4, CXCR5, TOX
Canonical Marker Genes: unknown
Rationale: NA

Set of Labels Description: Single-cell transcriptome analysis of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19
Annotation Method: both
Algorithm Name: Azimuth
Algorithm Version: v1
Algorithm URL: https://azimuth.hubmapconsortium.org/