CeLaVi

CeLaVi visualizes cell lineage trees in three-dimensional spatial context to integrate lineage, spatial coordinates, and cellular attributes for analysis of developmental and genetic relationships.

Key Features:

• Cell lineage tree representation: Represents branching events and annotates clone depth within lineage trees.
• Spatial distribution mapping: Maps spatial distribution of cell clones at multiple lineage depths onto 3D coordinates.
• Lineage-based coloring: Assigns colors to cells based on lineage relationships to distinguish clones.
• Multi-attribute mapping: Overlays gene expression levels, annotated cell types, and tissue layer information onto spatial cell representations.
• Annotation of cells and clones: Attaches annotations to selected cells or clones for targeted analysis.
• Integration of microscopy and molecular recorder data: Combines lineage and spatial data derived from live microscopy and molecular recorders.

Scientific Applications:

• Developmental studies: Investigates how cells differentiate and organize during development by reconstructing division histories from imaging and molecular recorder data.
• Cancer research: Traces lineage and spatial distribution of cancerous cells to study tumor progression and clonal architecture.
• Stem cell research: Analyzes stem cell differentiation pathways and spatial contexts across tissues.

Methodology:

Integrates lineage, spatial, and cellular identity datasets derived from genetics and imaging sources to generate combined visualizations of lineage and spatial information.