spatial-transcriptomics

What problem does it solve?

Spatial transcriptomics workflows are often scattered across heterogeneous tools and notes; this Skill provides a structured, repeatable pipeline for preprocessing, domain detection, deconvolution, neighborhood analysis, and publication-ready maps.

Core Features & Use Cases

• Spatial preprocessing and normalization that preserve spatial coordinates
• Domain detection and deconvolution to infer cell-type composition in tissue spots
• Neighborhood analysis and generation of publication-ready spatial maps
• Use case: analyze a tissue section to identify spatial domains and associated cell-type enrichment

Quick Start

Begin by validating spatial inputs and then run the domain detection workflow on your spatial expression data using the preferred scanpy-like tools.