CytoMAP

CytoMAP enables quantitative spatial analysis of cellular patterning and tissue architecture from highly multiplexed imaging data.

Key Features:

• Histo-cytometric multidimensional analysis: Integrates multidimensional cellular measurements with spatial coordinates to relate phenotype and position.
• Data clustering: Applies clustering to group cells by multidimensional measurements.
• Positional correlation: Computes positional correlations to quantify spatial relationships among cells.
• Dimensionality reduction: Uses dimensionality reduction to visualize and analyze high-dimensional cellular features.
• 2D/3D region reconstruction: Reconstructs 2D and 3D tissue regions to delineate spatial compartments.
• Localized network identification: Identifies localized cellular networks and tissue microenvironments.
• Input data: Processes highly multiplexed imaging datasets as primary input.
• Cellular positioning and interaction analysis: Quantifies cellular positioning and cell–cell interactions within tissue architecture.

Scientific Applications:

• Murine lymph node microanatomy: Analyzed murine lymph nodes to study the microanatomy of innate immune subsets and myeloid cell organization.
• Migratory dendritic cell segregation: Revealed mutually exclusive segregation of migratory dendritic cells (DCs) within lymph nodes.
• SIRPα^- dermal DC compartmentalization: Detected regionalized compartmentalization of SIRPα^- dermal DCs.
• Resident DC association with vasculature: Identified preferential association of resident DCs with specific LN vasculature.

Methodology:

Performs histo-cytometric multidimensional analysis combining data clustering, positional correlation, dimensionality reduction, and 2D/3D region reconstruction.