Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch5:AIN-01-0039:kidney
bronze acute kidney injury ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch5_003_image': DataTree[cyx] (35, 1547, 679), (35, 773, 339), (35, 386, 169), (35, 193, 84), (35, 96, 42)
│ ├── 'img_Batch5_004_image': DataTree[cyx] (35, 2674, 703), (35, 1337, 351), (35, 668, 175), (35, 334, 87), (35, 167, 43)
│ ├── 'img_Batch5_005_image': DataTree[cyx] (35, 795, 1031), (35, 397, 515), (35, 198, 257), (35, 99, 128), (35, 49, 64)
│ └── 'img_Batch5_006_image': DataTree[cyx] (35, 1225, 1261), (35, 612, 630), (35, 306, 315), (35, 153, 157), (35, 76, 78)
├── Labels
│ ├── 'img_Batch5_003_cells_labels': DataTree[yx] (1547, 679), (773, 339), (386, 169), (193, 84), (96, 42)
│ ├── 'img_Batch5_004_cells_labels': DataTree[yx] (2674, 703), (1337, 351), (668, 175), (334, 87), (167, 43)
│ ├── 'img_Batch5_005_cells_labels': DataTree[yx] (795, 1031), (397, 515), (198, 257), (99, 128), (49, 64)
│ └── 'img_Batch5_006_cells_labels': DataTree[yx] (1225, 1261), (612, 630), (306, 315), (153, 157), (76, 78)
├── Shapes
│ ├── 'img_Batch5_003_cell_boundaries': GeoDataFrame shape: (3545, 2) (2D shapes)
│ ├── 'img_Batch5_004_cell_boundaries': GeoDataFrame shape: (7947, 2) (2D shapes)
│ ├── 'img_Batch5_005_cell_boundaries': GeoDataFrame shape: (2670, 2) (2D shapes)
│ └── 'img_Batch5_006_cell_boundaries': GeoDataFrame shape: (4536, 2) (2D shapes)
└── Tables
└── 'table': AnnData (18698, 35)
with coordinate systems:
▸ 'img_Batch5_003', with elements:
img_Batch5_003_image (Images), img_Batch5_003_cells_labels (Labels), img_Batch5_003_cell_boundaries (Shapes)
▸ 'img_Batch5_004', with elements:
img_Batch5_004_image (Images), img_Batch5_004_cells_labels (Labels), img_Batch5_004_cell_boundaries (Shapes)
▸ 'img_Batch5_005', with elements:
img_Batch5_005_image (Images), img_Batch5_005_cells_labels (Labels), img_Batch5_005_cell_boundaries (Shapes)
▸ 'img_Batch5_006', with elements:
img_Batch5_006_image (Images), img_Batch5_006_cells_labels (Labels), img_Batch5_006_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("FP0jnyBoR7aBtMNr0000")
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("FP0jnyBoR7aBtMNr") # 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 FP0jnyBoR7aBtMNr0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/FP0jnyBoR7aBtMNr
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid FP0jnyBoR7aBtMNrLicense: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Condition
- acute kidney injury
- Modality
- protein
- Observations (cells)
- 18,698
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 130 MB
- Sample ID
- S-BIAD3694:discovery:Batch5:AIN-01-0039: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