tysserand

tysserand reconstructs spatial networks from spatially resolved omics experiments to enable analysis of spatial organization, cellular interactions, and tissue architecture.

Key Features:

• Integration of Multiple Methods: Implements multiple methodologies within a unified framework for network reconstruction from spatial omics data.
• Parameter Optimization: Enables selection and tuning of reconstruction parameters to improve robustness and accuracy of networks.
• Data Cleaning and Integration: Provides functionalities for cleaning reconstructed networks and integrating network data with other analysis libraries.
• Community-Driven Development: Accepts contributed reconstruction methods from the scientific community to extend methodological options.

Scientific Applications:

• Spatial omics analysis: Reconstructs networks from spatially resolved omics data to study spatial organization within tissues.
• Cellular interaction and tissue architecture studies: Infers cellular interactions and tissue architecture from spatial networks derived from omics experiments.
• Developmental biology, cancer research, and regenerative medicine: Supports investigation of disease mechanisms and developmental processes at spatial resolution relevant to these fields.

Methodology:

Integration of diverse computational techniques to reconstruct spatial networks from omics data, iterative refinement of network models by parameter adjustment, and incorporation of contributed methods.