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Spatial-omics pipeline and analysis

sopa_logo

Built on top of SpatialData, Sopa enables processing and analyses of image-based spatial omics using a standard data structure and output. We currently support the following technologies: Xenium, MERSCOPE, CosMX, PhenoCycler, MACSIMA, Hyperion. Sopa was designed for generability and low memory consumption on large images (scales to 1TB+ images).

The pipeline outputs contain: (i) Xenium Explorer files for interactive visualization, (ii) an HTML report for quick quality controls, and (iii) a SpatialData .zarr directory for further analyses.

Overview

The following illustration describes the main steps of sopa:

sopa_overview

Why use sopa

  • sopa is designed to be memory-efficient, and it scales to large datasets with millions of cells
  • Depending on your need, you can use our Snakemake pipeline, our CLI, or our API
  • It's straightforward to move on to another spatial omics technology since sopa is general to every image-based spatial omics
  • You can open any data with the Xenium Explorer, which is a user-friendly software with many functions
  • Spatial statistics are optimized since geometric operations use shapely internally
  • You can customize sopa and add your own segmentation or annotation tool if desired
  • sopa integrates naturally with other community tools such as Scanpy or Squidpy.