HCA Gut Cell Atlas v1 Myeloid Lineage

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Cell Metadata

Monocytes

Ontology Term: monocyteCL:0000576
Synonyms Terms that have the same, or nearly the same, meaning as the selected cell type.: classical monocytes, intermediate monocytes, nonclassical monocytes
Category Class of which the cell type is a subclass.: myeloid cellCL:0000763
Ontology Assessment Disagreements with any aspect of the Cell Ontology.: —
Marker Gene Evidence Gene markers used by researcher to assign this cell annotation.: CD14, FCN1, LYST, AREG, PLAUR, CD300E, VCAN
Canonical Marker Genes: CD14, LST1, S100A8
Rationale: These clusters have high CD14, FCN1, LST1, VCAN, and inflammatory chemokine/adaptive-interface genes, and include classical and nonclassical states. May be possible to further subdivide into classical/nonclassical subtypes
Rationale DOI: 10.1038/s41586-021-03852-1

Set of Labels Description: Cell annotations (Prelim annotation) are based on the finest possible label that could be used to describe each of the ~500 clusters found during integration and subclustering
Annotation Method: both
Algorithm Name: scVI
Algorithm Version: 1.3.2
Algorithm URL: https://github.com/scverse/scvi-tools

Ontology Term: monocyteCL:0000576
Synonyms Terms that have the same, or nearly the same, meaning as the selected cell type.: classical monocytes, intermediate monocytes, nonclassical monocytes
Category Class of which the cell type is a subclass.: myeloid cellCL:0000763
Ontology Assessment Disagreements with any aspect of the Cell Ontology.: —
Marker Gene Evidence Gene markers used by researcher to assign this cell annotation.: CD14, FCN1, LYST, AREG, PLAUR, CD300E, VCAN
Canonical Marker Genes: CD14, LST1, S100A8
Rationale: These clusters have high CD14, FCN1, LST1, VCAN, and inflammatory chemokine/adaptive-interface genes, and include classical and nonclassical states. May be possible to further subdivide into classical/nonclassical subtypes
Rationale DOI: 10.1038/s41586-021-03852-1

Set of Labels Description: Cell annotations (Prelim annotation) are based on the finest possible label that could be used to describe each of the ~500 clusters found during integration and subclustering
Annotation Method: both
Algorithm Name: scVI
Algorithm Version: 1.3.2
Algorithm URL: https://github.com/scverse/scvi-tools