Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch21:L115:kidney
bronze ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch21_011_image': DataTree[cyx] (35, 4226, 622), (35, 2113, 311), (35, 1056, 155), (35, 528, 77), (35, 264, 38)
│ ├── 'img_Batch21_012_image': DataTree[cyx] (35, 452, 718), (35, 226, 359), (35, 113, 179), (35, 56, 89), (35, 28, 44)
│ ├── 'img_Batch21_013_image': DataTree[cyx] (35, 469, 1075), (35, 234, 537), (35, 117, 268), (35, 58, 134), (35, 29, 67)
│ └── 'img_Batch21_014_image': DataTree[cyx] (35, 604, 711), (35, 302, 355), (35, 151, 177), (35, 75, 88), (35, 37, 44)
├── Labels
│ ├── 'img_Batch21_011_cells_labels': DataTree[yx] (4226, 622), (2113, 311), (1056, 155), (528, 77), (264, 38)
│ ├── 'img_Batch21_012_cells_labels': DataTree[yx] (452, 718), (226, 359), (113, 179), (56, 89), (28, 44)
│ ├── 'img_Batch21_013_cells_labels': DataTree[yx] (469, 1075), (234, 537), (117, 268), (58, 134), (29, 67)
│ └── 'img_Batch21_014_cells_labels': DataTree[yx] (604, 711), (302, 355), (151, 177), (75, 88), (37, 44)
├── Shapes
│ ├── 'img_Batch21_011_cell_boundaries': GeoDataFrame shape: (12398, 2) (2D shapes)
│ ├── 'img_Batch21_012_cell_boundaries': GeoDataFrame shape: (1440, 2) (2D shapes)
│ ├── 'img_Batch21_013_cell_boundaries': GeoDataFrame shape: (2011, 2) (2D shapes)
│ └── 'img_Batch21_014_cell_boundaries': GeoDataFrame shape: (1674, 2) (2D shapes)
└── Tables
└── 'table': AnnData (17523, 35)
with coordinate systems:
▸ 'img_Batch21_011', with elements:
img_Batch21_011_image (Images), img_Batch21_011_cells_labels (Labels), img_Batch21_011_cell_boundaries (Shapes)
▸ 'img_Batch21_012', with elements:
img_Batch21_012_image (Images), img_Batch21_012_cells_labels (Labels), img_Batch21_012_cell_boundaries (Shapes)
▸ 'img_Batch21_013', with elements:
img_Batch21_013_image (Images), img_Batch21_013_cells_labels (Labels), img_Batch21_013_cell_boundaries (Shapes)
▸ 'img_Batch21_014', with elements:
img_Batch21_014_image (Images), img_Batch21_014_cells_labels (Labels), img_Batch21_014_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("bGYoTkmRrSanHD0W0000")
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("bGYoTkmRrSanHD0W") # 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 bGYoTkmRrSanHD0W0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/bGYoTkmRrSanHD0W
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid bGYoTkmRrSanHD0WLicense: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Modality
- protein
- Observations (cells)
- 17,523
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 207 MB
- Sample ID
- S-BIAD3694:discovery:Batch21:L115: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