Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch3:AIN-01-0050:kidney
bronze acute tubulointerstitial nephritis ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch3_001_image': DataTree[cyx] (35, 1674, 834), (35, 837, 417), (35, 418, 208), (35, 209, 104), (35, 104, 52)
│ ├── 'img_Batch3_002_image': DataTree[cyx] (35, 2294, 780), (35, 1147, 390), (35, 573, 195), (35, 286, 97), (35, 143, 48)
│ ├── 'img_Batch3_003_image': DataTree[cyx] (35, 3583, 786), (35, 1791, 393), (35, 895, 196), (35, 447, 98), (35, 223, 49)
│ └── 'img_Batch3_004_image': DataTree[cyx] (35, 1533, 922), (35, 766, 461), (35, 383, 230), (35, 191, 115), (35, 95, 57)
├── Labels
│ ├── 'img_Batch3_001_cells_labels': DataTree[yx] (1674, 834), (837, 417), (418, 208), (209, 104), (104, 52)
│ ├── 'img_Batch3_002_cells_labels': DataTree[yx] (2294, 780), (1147, 390), (573, 195), (286, 97), (143, 48)
│ ├── 'img_Batch3_003_cells_labels': DataTree[yx] (3583, 786), (1791, 393), (895, 196), (447, 98), (223, 49)
│ └── 'img_Batch3_004_cells_labels': DataTree[yx] (1533, 922), (766, 461), (383, 230), (191, 115), (95, 57)
├── Shapes
│ ├── 'img_Batch3_001_cell_boundaries': GeoDataFrame shape: (8224, 2) (2D shapes)
│ ├── 'img_Batch3_002_cell_boundaries': GeoDataFrame shape: (8764, 2) (2D shapes)
│ ├── 'img_Batch3_003_cell_boundaries': GeoDataFrame shape: (13531, 2) (2D shapes)
│ └── 'img_Batch3_004_cell_boundaries': GeoDataFrame shape: (4309, 2) (2D shapes)
└── Tables
└── 'table': AnnData (34828, 35)
with coordinate systems:
▸ 'img_Batch3_001', with elements:
img_Batch3_001_image (Images), img_Batch3_001_cells_labels (Labels), img_Batch3_001_cell_boundaries (Shapes)
▸ 'img_Batch3_002', with elements:
img_Batch3_002_image (Images), img_Batch3_002_cells_labels (Labels), img_Batch3_002_cell_boundaries (Shapes)
▸ 'img_Batch3_003', with elements:
img_Batch3_003_image (Images), img_Batch3_003_cells_labels (Labels), img_Batch3_003_cell_boundaries (Shapes)
▸ 'img_Batch3_004', with elements:
img_Batch3_004_image (Images), img_Batch3_004_cells_labels (Labels), img_Batch3_004_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("RlcYHUgh7ShILzqx0000")
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("RlcYHUgh7ShILzqx") # 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 RlcYHUgh7ShILzqx0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/RlcYHUgh7ShILzqx
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid RlcYHUgh7ShILzqxLicense: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Condition
- acute tubulointerstitial nephritis
- Modality
- protein
- Observations (cells)
- 34,828
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 273 MB
- Sample ID
- S-BIAD3694:discovery:Batch3:AIN-01-0050: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