Cellar

Cellar assigns cell types by integrating multi-omics single-cell sequencing and spatial proteomics data to support annotation of cellular identity in single-cell studies.

Key Features:

• Comprehensive analysis support: Supports the analysis workflow from initial data processing through cell-type annotation.
• Multi-omics compatibility: Integrates diverse molecular signals from multi-omics single-cell sequencing datasets.
• Spatial proteomics integration: Incorporates spatial proteomics measurements to annotate cell types within tissue context.
• Annotated HuBMAP reference datasets: Includes annotated Human Biomolecular Atlas Program (HuBMAP) datasets as reference resources.

Scientific Applications:

• HuBMAP dataset annotation: Annotation of HuBMAP datasets derived from multi-omics single-cell sequencing and spatial proteomics.
• Cellular heterogeneity and tissue architecture analysis: Characterization of cellular heterogeneity and tissue architecture using integrated molecular and spatial data.

Methodology:

Cellar leverages advanced computational algorithms to assign cell types by integrating molecular signals from multi-omics single-cell sequencing and spatial proteomics.