spatialdata_io.stereoseq

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spatialdata_io.stereoseq#

spatialdata_io.stereoseq(path, dataset_id=None, read_square_bin=True, optional_tif=False, imread_kwargs=mappingproxy({}), image_models_kwargs=mappingproxy({}))#

Read Stereo-seq formatted dataset.

Parameters:

  • path (str | Path) – Path to the directory containing the data.

  • dataset_id (str | None (default: None)) – Dataset identifier. If not given will be determined automatically.

  • read_square_bin (bool (default: True)) – If True, will read the square bin '.gef' file and build corresponding points element.

  • optional_tif (bool (default: False)) – If True, will read '_tissue_cut.tif' files.

  • imread_kwargs (Mapping[str, Any] (default: mappingproxy({}))) – Keyword arguments passed to dask_image.imread.imread().

  • image_models_kwargs (Mapping[str, Any] (default: mappingproxy({}))) – Keyword arguments passed to spatialdata.models.Image2DModel.

Return type:

SpatialData

Returns:

: spatialdata.SpatialData

Notes

The cell segmentation, which encodes the background as 0 and the cells as 1, is parsed as an image (i.e. (c, y, x)) object and not as labels object (i.e. (y, x)). If you want to visualize this binary image with napari you will have to adjust the color limit to be able to see the cells.

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