PhenoCycler-Fusion
Human lymph node
S-BIAD2100:Burkitt_5_2
bronze Interactive viewer Burkitt lymphoma Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'core_image': DataTree[cyx] (56, 3000, 3000), (56, 1500, 1500), (56, 750, 750)
├── Labels
│ └── 'cell_labels': DataTree[yx] (3000, 3000), (1500, 1500), (750, 750)
├── Shapes
│ └── 'cell_circles': GeoDataFrame shape: (14109, 2) (2D shapes)
└── Tables
└── 'table': AnnData (14109, 56)
with coordinate systems:
▸ 'global', with elements:
core_image (Images), cell_labels (Labels), cell_circles (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("X9Kgcatal2sSvfOV0000")
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("X9Kgcatal2sSvfOV") # 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 X9Kgcatal2sSvfOV0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/X9Kgcatal2sSvfOV
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid X9Kgcatal2sSvfOVLicense: CC0 1.0
Metadata
- Technology
- PhenoCycler-Fusion
- Organism
- human
- Tissue
- lymph node
- Condition
- Burkitt lymphoma
- Modality
- protein
- Observations (cells)
- 14,109
- Tier
- bronze
- Chemistry
- PhenoCycler-Fusion 1
- Staining
- IF
- Size
- 161 MB
- Sample ID
- S-BIAD2100:Burkitt_5_2
- License
- CC0 1.0
- Published
- Feb 5, 2026
Cite this dataset
doi.org/10.1101/2025.04.29.651202 ↗ BibTeX
@article{bia:S-BIAD2100,
doi = {10.1101/2025.04.29.651202},
title = {S-BIAD2100:LN_6_1},
year = {2025}
}Source: BioImage Archive ↗ · License: CC0 1.0 ↗ · Reprocessed to SpatialData by SpatialData-DB