iIMPACT

iIMPACT integrates image and molecular profiles to identify histology-based spatial domains and detect domain-specific differentially expressed genes in spatial transcriptomics analysis.

Key Features:

• Image-Molecular Integration: Combines AI-reconstructed histology images with spatial context of gene expression measurements.
• Spatial Domain Identification: Identifies and defines histology-based spatial domains using integrated image and molecular data.
• Differential Expression Analysis: Detects domain-specific differentially expressed genes within identified spatial domains.
• Multi-stage Statistical Framework: Employs a multi-stage statistical method for spatial transcriptomics analysis.

Scientific Applications:

• Spatial Transcriptomics Analysis: Enables analysis of cellular spatial organization and landscape of functional genes within spatial transcriptomics data.
• Tissue Morphology-Gene Expression Integration: Exploits morphological features from histology images to improve accuracy and interpretability beyond molecular-only clustering approaches.

Methodology:

iIMPACT is a multi-stage statistical method that integrates AI-reconstructed histology images and spatial context of gene expression measurements to identify spatial domains and detect domain-specific differentially expressed genes.