addROI_omero

addROI_omero ¶

addROI_omero(
    data,
    roi,
    xCoordinate="X_centroid",
    yCoordinate="Y_centroid",
    imageId="imageid",
    namingColumn="Name",
    subset=None,
    overwrite=True,
    label="ROI",
    bufferRoi=0,
    bufferRegions=None,
    nJobs=-1,
    verbose=False,
    outputDir=None,
    sdataTable=None,
)

Label cells by the OMERO ROI polygon they fall inside.

Export your ROIs from OMERO, pass the table here, and every cell gets the name of the region containing it — or 'Other' when it falls outside all of them. Polygons are parsed from WKT and tested point-in-polygon with shapely.

The ROI table needs a geometry column, found under any of geometry, polygon, or roi (case-insensitively), plus a name column given by namingColumn.

Parameters:

Name	Type	Description	Default
`data`	`(AnnData \| SpatialData \| str, required)`	The cell table. An `AnnData`, a path to an `.h5ad` file, a `SpatialData` object, or a path to a `.zarr` SpatialData store.	required
`roi`	`(DataFrame, required)`	The ROI export: one row per region, with a WKT geometry column and a name column.	required
`xCoordinate`	`str`	Column in `obs` holding x positions.	`'X_centroid'`
`yCoordinate`	`str`	Column in `obs` holding y positions.	`'Y_centroid'`
`imageId`	`str`	Column in `obs` holding image identifiers.	`'imageid'`
`namingColumn`	`str`	Column in the ROI table holding each region's name.	`'Name'`
`subset`	`str \| list`	Only label cells from these images.	`None`
`overwrite`	`bool`	Replace an existing `obs[label]` column. With `False`, existing labels are kept and only unlabelled cells are updated.	`True`
`label`	`str`	Column in `obs` the region names are written to.	`'ROI'`
`bufferRoi`	`float`	Grow (or, when negative, shrink) every polygon by this distance before testing, so cells just outside a boundary can still be included.	`0`
`bufferRegions`	`dict`	Per-region buffers, `{region name: distance}`, overriding `bufferRoi` for the regions named.	`None`
`nJobs`	`int`	Workers for the point-in-polygon test. The default `-1` uses every core.	`-1`
`verbose`	`bool`	Print progress messages.	`False`
`outputDir`	`str`	Directory to write the updated object to. With `None` the object is returned instead.	`None`
`sdataTable`	`str`	Which `SpatialData` table to work on. The labelled table replaces the one in the container, so keep its `region_key` and `instance_key` columns intact.	`None`

Returns:

Name	Type	Description
`adata`	`AnnData \| SpatialData \| None`	The updated object with `obs[label]` naming each cell's region, or `'Other'`. `None` when `outputDir` is given.

Raises:

Type	Description
`ImportError`	When shapely is not installed. Install `scimappro[roi]`.
`ValueError`	When the ROI table has no geometry, polygon, or roi column.

Example

import pandas as pd

roi = pd.read_csv("rois_from_omero.csv")
adata = sp.helpers.addROI_omero(adata, roi=roi, label="ROI")
adata.obs["ROI"].value_counts()

sp.pl.spatialScatterPlot(adata, colorBy="ROI", s=3)

# Then search the rest of the slide for regions that look like one of them.
adata = sp.tl.spatialSimilarityLookup(adata, roiColumn="ROI")