Visium

Human amygdala

GSM9937036

silver Interactive viewer H&E No linked publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9937036_Br6471-V13F27-366_C1_full_image': DataTree[cyx] (3, 27876, 26146), (3, 13938, 13073), (3, 6969, 6536), (3, 3484, 3268), (3, 1742, 1634)
│     ├── 'GSM9937036_Br6471-V13F27-366_C1_hires_image': DataArray[cyx] (3, 2000, 1876)
│     └── 'GSM9937036_Br6471-V13F27-366_C1_lowres_image': DataArray[cyx] (3, 600, 563)
├── Shapes
│     └── 'GSM9937036_Br6471-V13F27-366_C1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4992, 36601)
with coordinate systems:
    ▸ 'GSM9937036_Br6471-V13F27-366_C1', with elements:
        GSM9937036_Br6471-V13F27-366_C1_full_image (Images), GSM9937036_Br6471-V13F27-366_C1_hires_image (Images), GSM9937036_Br6471-V13F27-366_C1_lowres_image (Images), GSM9937036_Br6471-V13F27-366_C1 (Shapes)
    ▸ 'GSM9937036_Br6471-V13F27-366_C1_downscaled_hires', with elements:
        GSM9937036_Br6471-V13F27-366_C1_hires_image (Images), GSM9937036_Br6471-V13F27-366_C1 (Shapes)
    ▸ 'GSM9937036_Br6471-V13F27-366_C1_downscaled_lowres', with elements:
        GSM9937036_Br6471-V13F27-366_C1_lowres_image (Images), GSM9937036_Br6471-V13F27-366_C1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("TiudslPJheykXs4v0000")
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("TiudslPJheykXs4v")   # 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 TiudslPJheykXs4v0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/TiudslPJheykXs4v

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid TiudslPJheykXs4v

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: 26,146 × 27,876 px
mpp: 0.305 µm/px
Size: 2.0 GB
Sample ID: GSM9937036
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