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Visium

Mouse cardiac ventricle

GSM7898096

silver Interactive viewer H&E No linked publication
Mouse cardiac ventricle preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM7898096_Visium_heart_undamaged_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM7898096_Visium_heart_undamaged_hires_image': DataArray[cyx] (3, 1983, 2000)
│     └── 'GSM7898096_Visium_heart_undamaged_lowres_image': DataArray[cyx] (3, 595, 600)
├── Shapes
│     └── 'GSM7898096_Visium_heart_undamaged': GeoDataFrame shape: (591, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (591, 19465)
with coordinate systems:
    ▸ 'GSM7898096_Visium_heart_undamaged', with elements:
        GSM7898096_Visium_heart_undamaged_full_image (Images), GSM7898096_Visium_heart_undamaged_hires_image (Images), GSM7898096_Visium_heart_undamaged_lowres_image (Images), GSM7898096_Visium_heart_undamaged (Shapes)
    ▸ 'GSM7898096_Visium_heart_undamaged_downscaled_hires', with elements:
        GSM7898096_Visium_heart_undamaged_hires_image (Images), GSM7898096_Visium_heart_undamaged (Shapes)
    ▸ 'GSM7898096_Visium_heart_undamaged_downscaled_lowres', with elements:
        GSM7898096_Visium_heart_undamaged_lowres_image (Images), GSM7898096_Visium_heart_undamaged (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("PE4OI6vhjMHL7ZtH")   # 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/PE4OI6vhjMHL7ZtH

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid PE4OI6vhjMHL7ZtH
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["PE4OI6vhjMHL7ZtH0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
Visium
Organism
mouse
Tissue
cardiac ventricle
Modality
RNA
Observations
591
Tier
silver
Chemistry
Visium v1
Resolution
2,000 × 1,983 px
mpp
1.344 µm/px
Size
33 MB
Sample ID
GSM7898096
License
unknown
Published
Nov 28, 2023

Cite this dataset

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

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