Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch19:AIN-02-0060:kidney
bronze acute tubulointerstitial nephritis ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch19_007_image': DataTree[cyx] (35, 779, 505), (35, 389, 252), (35, 194, 126), (35, 97, 63), (35, 48, 31)
│ ├── 'img_Batch19_008_image': DataTree[cyx] (35, 535, 621), (35, 267, 310), (35, 133, 155), (35, 66, 77), (35, 33, 38)
│ ├── 'img_Batch19_009_image': DataTree[cyx] (35, 661, 694), (35, 330, 347), (35, 165, 173), (35, 82, 86), (35, 41, 43)
│ └── 'img_Batch19_010_image': DataTree[cyx] (35, 565, 399), (35, 282, 199), (35, 141, 99), (35, 70, 49), (35, 35, 24)
├── Labels
│ ├── 'img_Batch19_007_cells_labels': DataTree[yx] (779, 505), (389, 252), (194, 126), (97, 63), (48, 31)
│ ├── 'img_Batch19_008_cells_labels': DataTree[yx] (535, 621), (267, 310), (133, 155), (66, 77), (33, 38)
│ ├── 'img_Batch19_009_cells_labels': DataTree[yx] (661, 694), (330, 347), (165, 173), (82, 86), (41, 43)
│ └── 'img_Batch19_010_cells_labels': DataTree[yx] (565, 399), (282, 199), (141, 99), (70, 49), (35, 24)
├── Shapes
│ ├── 'img_Batch19_007_cell_boundaries': GeoDataFrame shape: (2464, 2) (2D shapes)
│ ├── 'img_Batch19_008_cell_boundaries': GeoDataFrame shape: (2013, 2) (2D shapes)
│ ├── 'img_Batch19_009_cell_boundaries': GeoDataFrame shape: (2710, 2) (2D shapes)
│ └── 'img_Batch19_010_cell_boundaries': GeoDataFrame shape: (1785, 2) (2D shapes)
└── Tables
└── 'table': AnnData (8972, 35)
with coordinate systems:
▸ 'img_Batch19_007', with elements:
img_Batch19_007_image (Images), img_Batch19_007_cells_labels (Labels), img_Batch19_007_cell_boundaries (Shapes)
▸ 'img_Batch19_008', with elements:
img_Batch19_008_image (Images), img_Batch19_008_cells_labels (Labels), img_Batch19_008_cell_boundaries (Shapes)
▸ 'img_Batch19_009', with elements:
img_Batch19_009_image (Images), img_Batch19_009_cells_labels (Labels), img_Batch19_009_cell_boundaries (Shapes)
▸ 'img_Batch19_010', with elements:
img_Batch19_010_image (Images), img_Batch19_010_cells_labels (Labels), img_Batch19_010_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("vQzFkSFyJvlmoq2s0000")
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("vQzFkSFyJvlmoq2s") # 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 vQzFkSFyJvlmoq2s0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/vQzFkSFyJvlmoq2s
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid vQzFkSFyJvlmoq2sLicense: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Condition
- acute tubulointerstitial nephritis
- Modality
- protein
- Observations (cells)
- 8,972
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 66.4 MB
- Sample ID
- S-BIAD3694:discovery:Batch19:AIN-02-0060: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