StaVia

StaVia synergizes multi-faceted single-cell data with higher-order random walks that leverage the memory of cells' past states, fused with a cartographic Atlas View that offers intuitive graph visualization to capture relationships between cell populations based on spatial location, gene expression, and developmental stage.

Key Features:

• Higher-order random walks: Leverages the memory of cells' past states to model trajectories across single-cell atlases.
• Atlas View graph visualization: Provides intuitive cartographic visualization of cell atlas data.
• Spatially aware cartography: Captures relationships between cell populations based on spatial location as well as gene expression and developmental stage.
• Multi-faceted data integration: Integrates diverse single-cell data types including spatial and temporal information.

Scientific Applications:

• Single-cell atlas cartography: Enables visualization and analysis of trajectories across large single-cell atlases.
• Developmental biology: Demonstrated using zebrafish gastrulation data to dissect complex biological landscapes in both spatial and temporal contexts.
• Cell population relationship mapping: Captures relationships between cell populations across space, time, and gene expression dimensions.

Methodology:

StaVia employs higher-order random walks that leverage the memory of cells' past states, combined with an Atlas View graph visualization for cartographic representation of single-cell atlas data.