EMAGE

EMAGE maps in situ gene expression patterns from raw images onto standardized 3D virtual mouse embryo models across developmental stages to enable spatial analysis of gene expression.

Key Features:

• Spatial Integration: Extracts gene expression domains from raw in situ images and maps them into standard 3D virtual mouse embryo models across developmental stages.
• Anatomy Ontology: Employs an anatomy ontology to annotate spatial sites of gene expression and support text- and ontology-based queries.
• Spatial Search Algorithms: Implements refined local spatial similarity search algorithms and global spatial comparison methods for comparing expression patterns.
• Clustering Analysis: Uses hierarchical clustering to analyze spatial expression pattern relationships across multiple developmental stages.
• Data Integration: Integrates curated image data from multiple journals and the genome-wide EURExpress dataset (~19,000 genes) into its spatial framework.
• 3D Imaging (OPT): Incorporates full 3D images generated using optical projection tomography (OPT) for visualization and spatial mapping.
• Programmatic Access and Federation: Provides BioMart-based programmable access, web services, and federated query capabilities for integration with other BioMarts and access to annotated and unannotated datasets.
• Backend and Data Access: Refactored from an object-oriented to a relational model to enable SQL access and access via a Java API.

Scientific Applications:

• Embryonic development analysis: Enables spatial interrogation of gene expression dynamics during mouse embryogenesis.
• Gene function inference: Supports inference of gene function from spatial expression domains and comparative spatial patterns.
• Comparative spatial analysis: Facilitates local and global spatial comparisons and hierarchical clustering of expression patterns across stages and datasets.
• Genome-wide expression mapping: Allows genome-scale spatial mapping and interrogation through integration of the EURExpress dataset and OPT 3D images.

Methodology:

Extracts expression domains from raw in situ images, maps domains into standard 3D virtual embryo models, annotates sites with an anatomy ontology, applies local spatial similarity and global spatial comparison algorithms and hierarchical clustering, integrates the EURExpress dataset and OPT 3D images, and exposes data via BioMart/web services with a relational backend supporting SQL and a Java API.