Visium

Human lymph node

GSM8500534

bronze Interactive viewer H&E Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8500534_Cap.area1_LN_V1_hires_image': DataArray[cyx] (3, 1950, 2000)
│     └── 'GSM8500534_Cap.area1_LN_V1_lowres_image': DataArray[cyx] (3, 585, 600)
├── Shapes
│     └── 'GSM8500534_Cap.area1_LN_V1': GeoDataFrame shape: (3384, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (3384, 17943)
with coordinate systems:
    ▸ 'GSM8500534_Cap.area1_LN_V1', with elements:
        GSM8500534_Cap.area1_LN_V1_hires_image (Images), GSM8500534_Cap.area1_LN_V1_lowres_image (Images), GSM8500534_Cap.area1_LN_V1 (Shapes)
    ▸ 'GSM8500534_Cap.area1_LN_V1_downscaled_hires', with elements:
        GSM8500534_Cap.area1_LN_V1_hires_image (Images), GSM8500534_Cap.area1_LN_V1 (Shapes)
    ▸ 'GSM8500534_Cap.area1_LN_V1_downscaled_lowres', with elements:
        GSM8500534_Cap.area1_LN_V1_lowres_image (Images), GSM8500534_Cap.area1_LN_V1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("E3vtOZcj8Zj8w1lx0000")
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("E3vtOZcj8Zj8w1lx")   # 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 E3vtOZcj8Zj8w1lx0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/E3vtOZcj8Zj8w1lx

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid E3vtOZcj8Zj8w1lx

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Spatial transcriptomics characterization of ecosystems in the immune tumor microenvironment of diffuse large B-cell lymphoma→

9 datasets · other

Metadata

Technology: Visium
Organism: human
Tissue: lymph node
Modality: RNA
Observations (spots): 3,384
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 2,000 × 1,950 px
mpp: 3.655 µm/px
Size: 36.7 MB
Sample ID: GSM8500534
License: NCBI GEO policy
Published: Apr 29, 2026

Cite this dataset

doi.org/10.1080/2162402x.2026.2660418 ↗

BibTeX

@article{Diaz_Herrero_2026,
  title = {Spatial transcriptomics unveils immune cellular ecosystems associated with patient survival in diffuse large B-cell lymphoma},
  volume = {15},
  ISSN = {2162-402X},
  url = {http://dx.doi.org/10.1080/2162402x.2026.2660418},
  DOI = {10.1080/2162402x.2026.2660418},
  number = {1},
  journal = {OncoImmunology},
  publisher = {Informa UK Limited},
  author = {Diaz-Herrero, Alba and Pelaez-Prestel, Héctor Fernando and Massenet-Regad, Lucile and Veyssiere, Maëva and Calvani, Julien and Cristinelli, Caterina and Lehmann-Che, Jacqueline and Meignin, Véronique and Thieblemont, Catherine and Blanc, Véronique and Soumelis, Vassili and Tonnerre, Pierre},
  year = {2026},
  month = Apr
}

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