Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch23:AIN-02-0080:kidney
bronze acute kidney injury ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch23_016_image': DataTree[cyx] (35, 4612, 658), (35, 2306, 329), (35, 1153, 164), (35, 576, 82), (35, 288, 41)
│ ├── 'img_Batch23_017_image': DataTree[cyx] (35, 1363, 642), (35, 681, 321), (35, 340, 160), (35, 170, 80), (35, 85, 40)
│ ├── 'img_Batch23_018_image': DataTree[cyx] (35, 1248, 732), (35, 624, 366), (35, 312, 183), (35, 156, 91), (35, 78, 45)
│ └── 'img_Batch23_019_image': DataTree[cyx] (35, 1321, 780), (35, 660, 390), (35, 330, 195), (35, 165, 97), (35, 82, 48)
├── Labels
│ ├── 'img_Batch23_016_cells_labels': DataTree[yx] (4612, 658), (2306, 329), (1153, 164), (576, 82), (288, 41)
│ ├── 'img_Batch23_017_cells_labels': DataTree[yx] (1363, 642), (681, 321), (340, 160), (170, 80), (85, 40)
│ ├── 'img_Batch23_018_cells_labels': DataTree[yx] (1248, 732), (624, 366), (312, 183), (156, 91), (78, 45)
│ └── 'img_Batch23_019_cells_labels': DataTree[yx] (1321, 780), (660, 390), (330, 195), (165, 97), (82, 48)
├── Shapes
│ ├── 'img_Batch23_016_cell_boundaries': GeoDataFrame shape: (11864, 2) (2D shapes)
│ ├── 'img_Batch23_017_cell_boundaries': GeoDataFrame shape: (3725, 2) (2D shapes)
│ ├── 'img_Batch23_018_cell_boundaries': GeoDataFrame shape: (3145, 2) (2D shapes)
│ └── 'img_Batch23_019_cell_boundaries': GeoDataFrame shape: (3976, 2) (2D shapes)
└── Tables
└── 'table': AnnData (22710, 35)
with coordinate systems:
▸ 'img_Batch23_016', with elements:
img_Batch23_016_image (Images), img_Batch23_016_cells_labels (Labels), img_Batch23_016_cell_boundaries (Shapes)
▸ 'img_Batch23_017', with elements:
img_Batch23_017_image (Images), img_Batch23_017_cells_labels (Labels), img_Batch23_017_cell_boundaries (Shapes)
▸ 'img_Batch23_018', with elements:
img_Batch23_018_image (Images), img_Batch23_018_cells_labels (Labels), img_Batch23_018_cell_boundaries (Shapes)
▸ 'img_Batch23_019', with elements:
img_Batch23_019_image (Images), img_Batch23_019_cells_labels (Labels), img_Batch23_019_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("ETS4ujep0PgvpTSV0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("ETS4ujep0PgvpTSV") # stem uid: Lamin resolves it to the latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Shell
# sddb client: download the .zarr into data/
sddb-cli download ETS4ujep0PgvpTSV0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/ETS4ujep0PgvpTSV
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ETS4ujep0PgvpTSVLicense: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Condition
- acute kidney injury
- Modality
- protein
- Observations (cells)
- 22,710
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 185 MB
- Sample ID
- S-BIAD3694:discovery:Batch23:AIN-02-0080:kidney
- License
- CC0 1.0
- Published
- Aug 18, 2026
Cite this dataset
doi.org/10.1038/s41467-026-77210-y ↗ BibTeX
@article{bia:S-BIAD3694,
doi = {10.1038/s41467-026-77210-y},
title = {S-BIAD3694:discovery:Batch2:L108:kidney}
}Source: BioImage Archive ↗ · License: CC0 1.0 ↗ · Reprocessed to SpatialData by SpatialData-DB