snRNA-seq of human optic nerve and optic nerve head - all cells

Main

Cell Metadata

Cone_S

Ontology Term: S cone cellCL:0003050
Synonyms Terms that have the same, or nearly the same, meaning as the selected cell type.: S cone, S-(short-wavelength sensitive) cone, S-cone photoreceptor, S-cone, short wavelength sensitive cone, short- (S) wavelength-sensitive cone, short-wavelength sensitive cone, short-wavelength-sensitive (S) cone
Category Class of which the cell type is a subclass.: retinal cone cellCL:0000573
Ontology Assessment Disagreements with any aspect of the Cell Ontology.: —
Marker Gene Evidence Gene markers used by researcher to assign this cell annotation.: OPN1SW
Canonical Marker Genes: OPN1SW
Rationale: S Cone (short wavelength - cone) is one type of Cone cells. The marker for S Cone is OPN1SW.
Rationale DOI: https://doi.org/10.1101/2023.11.07.566105

Set of Labels Description: We used scVI for data integration and then manually annotated each cell cluster based on marker gene expression
Annotation Method: both
Algorithm Name: scVI
Algorithm Version: scvi-tools 1.3.0
Algorithm URL: https://github.com/scverse/scvi-tools

Main

Cell Metadata

Ontology Term: S cone cellCL:0003050
Synonyms Terms that have the same, or nearly the same, meaning as the selected cell type.: S cone, S-(short-wavelength sensitive) cone, S-cone photoreceptor, S-cone, short wavelength sensitive cone, short- (S) wavelength-sensitive cone, short-wavelength sensitive cone, short-wavelength-sensitive (S) cone
Category Class of which the cell type is a subclass.: retinal cone cellCL:0000573
Ontology Assessment Disagreements with any aspect of the Cell Ontology.: —
Marker Gene Evidence Gene markers used by researcher to assign this cell annotation.: OPN1SW
Canonical Marker Genes: OPN1SW
Rationale: S Cone (short wavelength - cone) is one type of Cone cells. The marker for S Cone is OPN1SW.
Rationale DOI: https://doi.org/10.1101/2023.11.07.566105

Set of Labels Description: We used scVI for data integration and then manually annotated each cell cluster based on marker gene expression
Annotation Method: both
Algorithm Name: scVI
Algorithm Version: scvi-tools 1.3.0
Algorithm URL: https://github.com/scverse/scvi-tools