Tooluniverse Spatial Transcriptomics

Handles the full pipeline for spatial transcriptomics data from platforms like 10x Visium, MERFISH, and Slide-seq. You get quality control, spatial clustering to identify tissue domains, detection of spatially variable genes using Moran's I, and cell-cell interaction mapping through ligand-receptor databases. The integration piece is solid: it can deconvolve cell types from scRNA-seq references using Cell2location or Tangram, then map those annotations onto tissue architecture. Built on squidpy and scanpy, so if you're already in that ecosystem it's a natural fit. The workflow is comprehensive but you'll need local Python for the heavy computation, while gene context and L-R databases hit ToolUniverse APIs.