Visium
Human amygdala
GSM9937032
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9937032_Br6471-V13F27-354_C1_full_image': DataTree[cyx] (3, 32481, 27721), (3, 16240, 13860), (3, 8120, 6930), (3, 4060, 3465), (3, 2030, 1732)
│ ├── 'GSM9937032_Br6471-V13F27-354_C1_hires_image': DataArray[cyx] (3, 2000, 1707)
│ └── 'GSM9937032_Br6471-V13F27-354_C1_lowres_image': DataArray[cyx] (3, 600, 512)
├── Shapes
│ └── 'GSM9937032_Br6471-V13F27-354_C1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 36601)
with coordinate systems:
▸ 'GSM9937032_Br6471-V13F27-354_C1', with elements:
GSM9937032_Br6471-V13F27-354_C1_full_image (Images), GSM9937032_Br6471-V13F27-354_C1_hires_image (Images), GSM9937032_Br6471-V13F27-354_C1_lowres_image (Images), GSM9937032_Br6471-V13F27-354_C1 (Shapes)
▸ 'GSM9937032_Br6471-V13F27-354_C1_downscaled_hires', with elements:
GSM9937032_Br6471-V13F27-354_C1_hires_image (Images), GSM9937032_Br6471-V13F27-354_C1 (Shapes)
▸ 'GSM9937032_Br6471-V13F27-354_C1_downscaled_lowres', with elements:
GSM9937032_Br6471-V13F27-354_C1_lowres_image (Images), GSM9937032_Br6471-V13F27-354_C1 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("nyOKMepdOCHdmfu3") # 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 Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/nyOKMepdOCHdmfu3
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nyOKMepdOCHdmfu3 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["nyOKMepdOCHdmfu30000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Multiscale spatial transcriptomics resolves the cellular and molecular architecture of the human amygdala [Visium]→ 48 datasets · replicates
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- amygdala
- Modality
- RNA
- Observations
- 4,992
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 20x
- Resolution
- 27,721 × 32,481 px
- mpp
- 0.306 µm/px
- Size
- 2.2 GB
- Sample ID
- GSM9937032
- License
- unknown
- Published
- Aug 24, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB