SOAPy

SOAPy offers methods for dissecting spatial architecture, dynamics, and communication in spatial omics data.

Key Features:

• Spatial domain identification: Identifies spatial domains in tissue microenvironments.
• Spatial expression tendency: Analyzes spatial expression tendencies across tissues.
• Spatiotemporal expression pattern: Characterizes spatiotemporal expression patterns in spatial omics data.
• Cellular co-localization: Identifies co-localization patterns of cells in spatial data.
• Multi-cellular niches: Detects and analyzes multi-cellular niches in tissue microenvironments.
• Cell-cell communication: Analyzes cell-cell communication from spatial omics data.

Scientific Applications:

• Tumor biology: Applies spatial omics analysis to understand tumor microenvironments.
• Developmental biology: Investigates tissue dynamics and architecture during development using spatial omics.
• Physiological and pathological contexts: Supports diverse areas in physiological and pathological research using spatial omics technologies.

Methodology:

Methods include spatial domain identification, spatial expression tendency analysis, spatiotemporal expression pattern analysis, cellular co-localization detection, multi-cellular niche identification, and cell-cell communication analysis.