Visium

Mouse lung

GSM9119670

bronze Interactive viewer H&E lung carcinoma Provisional

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9119670_AG-F-6091_hires_image': DataArray[cyx] (3, 2000, 1914)
│     └── 'GSM9119670_AG-F-6091_lowres_image': DataArray[cyx] (3, 600, 574)
├── Shapes
│     └── 'GSM9119670_AG-F-6091': GeoDataFrame shape: (2697, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2697, 32285)
with coordinate systems:
    ▸ 'GSM9119670_AG-F-6091', with elements:
        GSM9119670_AG-F-6091_hires_image (Images), GSM9119670_AG-F-6091_lowres_image (Images), GSM9119670_AG-F-6091 (Shapes)
    ▸ 'GSM9119670_AG-F-6091_downscaled_hires', with elements:
        GSM9119670_AG-F-6091_hires_image (Images), GSM9119670_AG-F-6091 (Shapes)
    ▸ 'GSM9119670_AG-F-6091_downscaled_lowres', with elements:
        GSM9119670_AG-F-6091_lowres_image (Images), GSM9119670_AG-F-6091 (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("K5L1PhWVJxnkBfUN")   # 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/K5L1PhWVJxnkBfUN

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid K5L1PhWVJxnkBfUN

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["K5L1PhWVJxnkBfUN0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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

Part of collection

A novel CAF population coordinates hyper-suppressive regulatory T cell recruitment and localization in lung cancer [Spatial Transcriptomics]→

2 datasets · other

Metadata

Technology: Visium
Organism: mouse
Tissue: lung
Condition: lung carcinoma
Modality: RNA
Observations: 2,697
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 1,914 × 2,000 px
mpp: 3.707 µm/px
Size: 29 MB
Sample ID: GSM9119670
License: unknown
Published: Jun 29, 2026

Cite this dataset

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

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