Imaging Mass Cytometry

Human kidney

S-BIAD3694:discovery:Batch20:AIN-02-0053:kidney

bronze acute tubulointerstitial nephritis ✓ Verified publication

Imaging Mass Cytometry

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'img_Batch20_001_image': DataTree[cyx] (35, 611, 717), (35, 305, 358), (35, 152, 179), (35, 76, 89), (35, 38, 44)
│     └── 'img_Batch20_002_image': DataTree[cyx] (35, 1103, 993), (35, 551, 496), (35, 275, 248), (35, 137, 124), (35, 68, 62)
├── Labels
│     ├── 'img_Batch20_001_cells_labels': DataTree[yx] (611, 717), (305, 358), (152, 179), (76, 89), (38, 44)
│     └── 'img_Batch20_002_cells_labels': DataTree[yx] (1103, 993), (551, 496), (275, 248), (137, 124), (68, 62)
├── Shapes
│     ├── 'img_Batch20_001_cell_boundaries': GeoDataFrame shape: (2050, 2) (2D shapes)
│     └── 'img_Batch20_002_cell_boundaries': GeoDataFrame shape: (5522, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (7572, 35)
with coordinate systems:
    ▸ 'img_Batch20_001', with elements:
        img_Batch20_001_image (Images), img_Batch20_001_cells_labels (Labels), img_Batch20_001_cell_boundaries (Shapes)
    ▸ 'img_Batch20_002', with elements:
        img_Batch20_002_image (Images), img_Batch20_002_cells_labels (Labels), img_Batch20_002_cell_boundaries (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("Jev86ujO3Cj3AMik0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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("Jev86ujO3Cj3AMik")   # 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download Jev86ujO3Cj3AMik0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/Jev86ujO3Cj3AMik

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Jev86ujO3Cj3AMik

Install (Python 3.12+) Docs →

License: CC0 1.0

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Part of collection

bia-s-biad3694→

67 datasets · publication

Metadata

Technology: Imaging Mass Cytometry
Organism: human
Tissue: kidney
Condition: acute tubulointerstitial nephritis
Modality: protein
Observations (cells): 7,572
Tier: bronze
Chemistry: IMC
Staining: Antibodies
Size: 59.3 MB
Sample ID: S-BIAD3694:discovery:Batch20:AIN-02-0053: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