Spatial-omics pipeline and analysis. Built on top of SpatialData, Sopa enables processing and analyses of spatial omics data with single-cell resolution (spatial transcriptomics or multiplex imaging data) using a standard data structure and output. We currently support the following technologies: Xenium, Visium HD, MERSCOPE, CosMX, PhenoCycler ...

Built on top of SpatialData, Sopa enables processing and analyses of spatial omics data with single-cell resolution (spatial transcriptomics or multiplex imaging data) using a standard data structure and output. We currently support the following technologies: Xenium, Visium HD, MERSCOPE, CosMX, PhenoCycler, MACSima, Hyperion.

Jun 11, 2024 · Built upon the universal SpatialData framework, Sopa optimizes tasks like segmentation, transcript/channel aggregation, annotation, and geometric/spatial analysis. Its output includes...

Sopa comes in three different flavours, each corresponding to a different use case: Snakemake pipeline: choose a config, and run our pipeline on your spatial data in a few minutes. See our snakemake tutorial.

Spatial join of two shapes GeoDataFrames, as in geopandas.sjoin. Shapes are automatically aligned on the same coordinate system (which can be chosen using the target_coordinate_system argument). Parameters: The GeoPandas type of join. By default, left geometries are retained.

Mar 13, 2025 · Spatial omics pipeline and analysis. Built on top of SpatialData, Sopa enables processing and analyses of spatial omics data with single-cell resolution (spatial transcriptomics or multiplex imaging data) using a standard data structure and output. We currently support the following technologies: Xenium, Visium HD, MERSCOPE, CosMX, PhenoCycler ...

Dec 23, 2023 · Built upon the universal SpatialData framework, Sopa optimizes tasks like segmentation, transcript/channel aggregation, annotation, and geometric/spatial analysis. Its output includes...

We introduce Sopa (https://github.com/gustaveroussy/sopa), a technology-invariant, memory-efficient pipeline with a unified visualizer for all image-based spatial omics. Built upon the universal SpatialData framework, Sopa optimizes tasks like segmentation, transcript/channel aggregation, annotation, and geometric/spatial analysis.

Jun 11, 2024 · Built upon the universal SpatialData framework, Sopa optimizes tasks like segmentation, transcript/channel aggregation, annotation, and geometric/spatial analysis. Its output includes user-friendly web reports and visualizer files, as well as comprehensive data files for in-depth analysis.

Oct 15, 2024 · Spatial elements keys are saved in sdata.attrs so that Sopa knows automatically which element should be used in which function. It is still possible to precise image_key / points_key / shapes_key if needed.