AtlasGrabber

AtlasGrabber enables high-throughput retrieval and comparative analysis of immunohistochemically stained tissue microarray images from the Human Protein Atlas to study protein expression and spatial localization in normal and cancerous tissues.

Key Features:

• High-throughput image analysis: Enables large-scale screening and processing of immunohistochemically stained tissue microarray images from the Human Protein Atlas.
• Gene-list based image retrieval: Fetches images from the HPA using predefined or user-specified gene lists to target specific proteins.
• Comparative visualization: Supports simultaneous comparison of multiple images (up to four) across tissues and between normal and cancer samples.
• Antibody and image filtering: Filters images by specific antibodies and image types to refine dataset selection.
• XML parser for HPA data: Parses Human Protein Atlas XML files to extract lists of available antibodies, images, and genes for specified tissues or cancer types.

Scientific Applications:

• Spatial proteomics analysis: Use IHC images to analyze protein localization and spatial distribution within tissue architecture.
• Biomarker discovery: Identify candidate protein markers by comparing expression patterns between normal and cancerous tissues.
• Comparative tissue and disease analysis: Compare protein expression across different tissues and between normal versus cancer states.
• Histopathological marker identification in prostate cancer: Detect basal-cell–specific markers and assess their presence or loss in prostate cancer samples (demonstrated by identification of six basal-cell markers, five absent in cancer cases).

Methodology:

Parses HPA XML files to extract antibodies, images, and gene lists; retrieves corresponding IHC tissue microarray images from the Human Protein Atlas based on specified genes; supports comparative analysis by presenting multiple images for side-by-side examination.