Visium

Human amygdala

GSM9937031

silver Interactive viewer H&E No linked publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9937031_Br6471-V13F27-354_B1_full_image': DataTree[cyx] (3, 32481, 27721), (3, 16240, 13860), (3, 8120, 6930), (3, 4060, 3465), (3, 2030, 1732)
│     ├── 'GSM9937031_Br6471-V13F27-354_B1_hires_image': DataArray[cyx] (3, 2000, 1707)
│     └── 'GSM9937031_Br6471-V13F27-354_B1_lowres_image': DataArray[cyx] (3, 600, 512)
├── Shapes
│     └── 'GSM9937031_Br6471-V13F27-354_B1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4992, 36601)
with coordinate systems:
    ▸ 'GSM9937031_Br6471-V13F27-354_B1', with elements:
        GSM9937031_Br6471-V13F27-354_B1_full_image (Images), GSM9937031_Br6471-V13F27-354_B1_hires_image (Images), GSM9937031_Br6471-V13F27-354_B1_lowres_image (Images), GSM9937031_Br6471-V13F27-354_B1 (Shapes)
    ▸ 'GSM9937031_Br6471-V13F27-354_B1_downscaled_hires', with elements:
        GSM9937031_Br6471-V13F27-354_B1_hires_image (Images), GSM9937031_Br6471-V13F27-354_B1 (Shapes)
    ▸ 'GSM9937031_Br6471-V13F27-354_B1_downscaled_lowres', with elements:
        GSM9937031_Br6471-V13F27-354_B1_lowres_image (Images), GSM9937031_Br6471-V13F27-354_B1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("v20ILoKiIGGf0w5z0000")
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("v20ILoKiIGGf0w5z")   # 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 v20ILoKiIGGf0w5z0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/v20ILoKiIGGf0w5z

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid v20ILoKiIGGf0w5z

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part 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 (spots): 4,992
Tier: silver
Chemistry: Visium v1
Magnification: 20x
Resolution: 27,721 × 32,481 px
mpp: 0.305 µm/px
Size: 2.5 GB
Sample ID: GSM9937031
License: NCBI GEO policy
Published: Aug 24, 2026

Cite this dataset

No linked publication found — please cite the data source: NCBI GEO ↗.

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB