Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch7:AIN-01-0082:kidney
bronze acute kidney injury ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch7_007_image': DataTree[cyx] (35, 4083, 374), (35, 2041, 187), (35, 1020, 93), (35, 510, 46), (35, 255, 23)
│ ├── 'img_Batch7_008_image': DataTree[cyx] (35, 2025, 1053), (35, 1012, 526), (35, 506, 263), (35, 253, 131), (35, 126, 65)
│ ├── 'img_Batch7_009_image': DataTree[cyx] (35, 1066, 956), (35, 533, 478), (35, 266, 239), (35, 133, 119), (35, 66, 59)
│ └── 'img_Batch7_010_image': DataTree[cyx] (35, 1212, 651), (35, 606, 325), (35, 303, 162), (35, 151, 81), (35, 75, 40)
├── Labels
│ ├── 'img_Batch7_007_cells_labels': DataTree[yx] (4083, 374), (2041, 187), (1020, 93), (510, 46), (255, 23)
│ ├── 'img_Batch7_008_cells_labels': DataTree[yx] (2025, 1053), (1012, 526), (506, 263), (253, 131), (126, 65)
│ ├── 'img_Batch7_009_cells_labels': DataTree[yx] (1066, 956), (533, 478), (266, 239), (133, 119), (66, 59)
│ └── 'img_Batch7_010_cells_labels': DataTree[yx] (1212, 651), (606, 325), (303, 162), (151, 81), (75, 40)
├── Shapes
│ ├── 'img_Batch7_007_cell_boundaries': GeoDataFrame shape: (6809, 2) (2D shapes)
│ ├── 'img_Batch7_008_cell_boundaries': GeoDataFrame shape: (4375, 2) (2D shapes)
│ ├── 'img_Batch7_009_cell_boundaries': GeoDataFrame shape: (3020, 2) (2D shapes)
│ └── 'img_Batch7_010_cell_boundaries': GeoDataFrame shape: (2990, 2) (2D shapes)
└── Tables
└── 'table': AnnData (17194, 35)
with coordinate systems:
▸ 'img_Batch7_007', with elements:
img_Batch7_007_image (Images), img_Batch7_007_cells_labels (Labels), img_Batch7_007_cell_boundaries (Shapes)
▸ 'img_Batch7_008', with elements:
img_Batch7_008_image (Images), img_Batch7_008_cells_labels (Labels), img_Batch7_008_cell_boundaries (Shapes)
▸ 'img_Batch7_009', with elements:
img_Batch7_009_image (Images), img_Batch7_009_cells_labels (Labels), img_Batch7_009_cell_boundaries (Shapes)
▸ 'img_Batch7_010', with elements:
img_Batch7_010_image (Images), img_Batch7_010_cells_labels (Labels), img_Batch7_010_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("uwZPyWv8PCMOHFp90000")
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("uwZPyWv8PCMOHFp9") # 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 uwZPyWv8PCMOHFp90000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/uwZPyWv8PCMOHFp9
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid uwZPyWv8PCMOHFp9License: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Condition
- acute kidney injury
- Modality
- protein
- Observations (cells)
- 17,194
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 168 MB
- Sample ID
- S-BIAD3694:discovery:Batch7:AIN-01-0082: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