Visium HD

Human lymph node

GSM9025383

bronze Interactive viewer H&E breast cancer Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9025383_LN2_hires_image': DataArray[cyx] (3, 4708, 6000)
│     └── 'GSM9025383_LN2_lowres_image': DataArray[cyx] (3, 471, 600)
├── Shapes
│     ├── 'GSM9025383_LN2_square_008um': GeoDataFrame shape: (526905, 1) (2D shapes)
│     └── 'GSM9025383_LN2_square_008um_for_vitessce': GeoDataFrame shape: (526905, 2) (2D shapes)
└── Tables
      └── 'square_008um': AnnData (526905, 18085)
with coordinate systems:
    ▸ 'GSM9025383_LN2', with elements:
        GSM9025383_LN2_hires_image (Images), GSM9025383_LN2_lowres_image (Images), GSM9025383_LN2_square_008um (Shapes), GSM9025383_LN2_square_008um_for_vitessce (Shapes)
    ▸ 'GSM9025383_LN2_downscaled_hires', with elements:
        GSM9025383_LN2_hires_image (Images), GSM9025383_LN2_square_008um (Shapes), GSM9025383_LN2_square_008um_for_vitessce (Shapes)
    ▸ 'GSM9025383_LN2_downscaled_lowres', with elements:
        GSM9025383_LN2_lowres_image (Images), GSM9025383_LN2_square_008um (Shapes), GSM9025383_LN2_square_008um_for_vitessce (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("3P9LWItd6nvb7TO90000")
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("3P9LWItd6nvb7TO9")   # 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 3P9LWItd6nvb7TO90000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/3P9LWItd6nvb7TO9

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 3P9LWItd6nvb7TO9

Install (Python 3.12+) Docs →

License: NCBI GEO policy

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

Breast Cancer Remodels Lymphatics in Sentinel Lymph Nodes→

4 datasets · comparison

Metadata

Technology: Visium HD
Organism: human
Tissue: lymph node
Condition: breast cancer
Modality: RNA
Observations (bins): 526,905
Tier: bronze
Resolution: 6,000 × 4,708 px
mpp: 1.406 µm/px
Size: 1.5 GB
Sample ID: GSM9025383
License: NCBI GEO policy
Published: Sep 2, 2025

Cite this dataset

doi.org/10.1038/s41467-025-64981-z ↗

BibTeX

@article{Eichin_2025,
  title = {Breast cancer remodels lymphatics in sentinel lymph nodes},
  volume = {16},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-025-64981-z},
  DOI = {10.1038/s41467-025-64981-z},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Eichin, Dominik and Lehotina, Diana and Kauko, Anni and Uenaka, Maki and Leppänen, Meri and Elima, Kati and Piipponen, Minna and Lönnberg, Tapio and Boström, Pia and Koskivuo, Ilkka and Aittokallio, Tero and Hollmén, Maija and Takeda, Akira and Jalkanen, Sirpa},
  year = {2025},
  month = Nov
}

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