ATHENA

ATHENA analyzes tumor heterogeneity from spatial omics measurements using graph-based representations and a suite of heterogeneity scores to quantify spatial patterns and cellular interactions in cancer tissue.

Key Features:

• Spatial omics support: Processes and analyzes spatial omics measurements to capture spatially resolved molecular information within tumor tissue.
• Graph-based tumor representation: Represents tumors as graphs to model spatial relationships among cells or spots.
• Heterogeneity scores: Computes a comprehensive suite of established and novel heterogeneity scores to quantify multiple dimensions of tumor complexity.
• Visualization: Provides methods for visualizing spatial characteristics and spatial distributions within tumor ecosystems.
• Data processing and analysis: Includes routines for processing spatial omics data and performing downstream analyses focused on tumor heterogeneity.
• Implementation: Implemented in Python.

Scientific Applications:

• Assessment of tumor heterogeneity: Quantifies spatially informed heterogeneity metrics to assess intra-tumor variability.
• Characterization of spatial distribution: Evaluates spatial distribution and interactions of cellular components within tumors.
• Analysis of tumor ecosystems: Investigates patterns and organization of cell populations and their spatial relationships in cancer tissue.

Methodology:

Constructs graph representations of tumors and computes a comprehensive set of established and novel heterogeneity scores, with computational routines implemented in Python.