Cell Taxonomy

Cell Taxonomy catalogs and characterizes cell types and their associated markers across species and tissues by integrating curated literature with single-cell transcriptomic data to support analysis of cellular heterogeneity, development, and tumorigenesis.

Key Features:

• Dataset scope: Contains a taxonomy of 3,143 distinct cell types with 26,613 associated cell markers across 257 conditions, 387 tissues, and 34 species, derived from 4,299 publications and ~3.5 million single-cell transcriptomic profiles.
• Multifaceted characterization: Provides comprehensive characterization of cell types and markers, including quality assessments of markers and the clusters they define.
• Cross-species comparison: Enables comparative analyses of cell types across different species to investigate conserved cellular functions.
• Cell composition analysis: Supports detailed examination of cell composition within tissues to inform studies of tissue architecture and function.
• Marker-based cellular similarity: Identifies analogous cell types across conditions or species based on shared marker profiles.
• Literature curation and data integration: Integrates curated literature evidence with empirical single-cell transcriptomic data to assemble and support the taxonomy.

Scientific Applications:

• Cellular heterogeneity: Dissects cellular heterogeneity at single-cell resolution across tissues and conditions.
• Developmental biology: Supports analysis of cell-type changes and trajectories during development.
• Tumorigenesis and oncology: Facilitates identification and comparison of tumor-associated cell types and markers for cancer research.
• Evolutionary biology: Enables comparative studies of conserved and divergent cell types across species.
• Tissue architecture and composition studies: Informs investigations of tissue-specific cell composition and organization.
• Regenerative medicine: Provides reference cell-type and marker information relevant to tissue repair and regeneration research.

Methodology:

Curated literature was integrated with single-cell transcriptomic profiles to construct a structured taxonomy, accompanied by quality assessments of markers and defined clusters.