Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch7:AIN-01-0115:kidney
bronze acute tubulointerstitial nephritis ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch7_001_image': DataTree[cyx] (35, 1250, 781), (35, 625, 390), (35, 312, 195), (35, 156, 97), (35, 78, 48)
│ ├── 'img_Batch7_002_image': DataTree[cyx] (35, 850, 1365), (35, 425, 682), (35, 212, 341), (35, 106, 170), (35, 53, 85)
│ ├── 'img_Batch7_003_image': DataTree[cyx] (35, 1070, 857), (35, 535, 428), (35, 267, 214), (35, 133, 107), (35, 66, 53)
│ ├── 'img_Batch7_004_image': DataTree[cyx] (35, 795, 986), (35, 397, 493), (35, 198, 246), (35, 99, 123), (35, 49, 61)
│ ├── 'img_Batch7_005_image': DataTree[cyx] (35, 752, 1000), (35, 376, 500), (35, 188, 250), (35, 94, 125), (35, 47, 62)
│ └── 'img_Batch7_006_image': DataTree[cyx] (35, 641, 967), (35, 320, 483), (35, 160, 241), (35, 80, 120), (35, 40, 60)
├── Labels
│ ├── 'img_Batch7_001_cells_labels': DataTree[yx] (1250, 781), (625, 390), (312, 195), (156, 97), (78, 48)
│ ├── 'img_Batch7_002_cells_labels': DataTree[yx] (850, 1365), (425, 682), (212, 341), (106, 170), (53, 85)
│ ├── 'img_Batch7_003_cells_labels': DataTree[yx] (1070, 857), (535, 428), (267, 214), (133, 107), (66, 53)
│ ├── 'img_Batch7_004_cells_labels': DataTree[yx] (795, 986), (397, 493), (198, 246), (99, 123), (49, 61)
│ ├── 'img_Batch7_005_cells_labels': DataTree[yx] (752, 1000), (376, 500), (188, 250), (94, 125), (47, 62)
│ └── 'img_Batch7_006_cells_labels': DataTree[yx] (641, 967), (320, 483), (160, 241), (80, 120), (40, 60)
├── Shapes
│ ├── 'img_Batch7_001_cell_boundaries': GeoDataFrame shape: (5543, 2) (2D shapes)
│ ├── 'img_Batch7_002_cell_boundaries': GeoDataFrame shape: (4370, 2) (2D shapes)
│ ├── 'img_Batch7_003_cell_boundaries': GeoDataFrame shape: (4038, 2) (2D shapes)
│ ├── 'img_Batch7_004_cell_boundaries': GeoDataFrame shape: (4121, 2) (2D shapes)
│ ├── 'img_Batch7_005_cell_boundaries': GeoDataFrame shape: (4116, 2) (2D shapes)
│ └── 'img_Batch7_006_cell_boundaries': GeoDataFrame shape: (3450, 2) (2D shapes)
└── Tables
└── 'table': AnnData (25638, 35)
with coordinate systems:
▸ 'img_Batch7_001', with elements:
img_Batch7_001_image (Images), img_Batch7_001_cells_labels (Labels), img_Batch7_001_cell_boundaries (Shapes)
▸ 'img_Batch7_002', with elements:
img_Batch7_002_image (Images), img_Batch7_002_cells_labels (Labels), img_Batch7_002_cell_boundaries (Shapes)
▸ 'img_Batch7_003', with elements:
img_Batch7_003_image (Images), img_Batch7_003_cells_labels (Labels), img_Batch7_003_cell_boundaries (Shapes)
▸ 'img_Batch7_004', with elements:
img_Batch7_004_image (Images), img_Batch7_004_cells_labels (Labels), img_Batch7_004_cell_boundaries (Shapes)
▸ 'img_Batch7_005', with elements:
img_Batch7_005_image (Images), img_Batch7_005_cells_labels (Labels), img_Batch7_005_cell_boundaries (Shapes)
▸ 'img_Batch7_006', with elements:
img_Batch7_006_image (Images), img_Batch7_006_cells_labels (Labels), img_Batch7_006_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("ipmsbYiUF5ppd6G60000")
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("ipmsbYiUF5ppd6G6") # 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 ipmsbYiUF5ppd6G60000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/ipmsbYiUF5ppd6G6
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ipmsbYiUF5ppd6G6License: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Condition
- acute tubulointerstitial nephritis
- Modality
- protein
- Observations (cells)
- 25,638
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 191 MB
- Sample ID
- S-BIAD3694:discovery:Batch7:AIN-01-0115: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