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Visium

Mouse ovary

GSM8450580

bronze Interactive viewer H&E ovarian cancer Provisional
Mouse ovary preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM8450580_OV_FC_ACT_hires_image': DataArray[cyx] (3, 1974, 2000)
│     └── 'GSM8450580_OV_FC_ACT_lowres_image': DataArray[cyx] (3, 592, 600)
├── Shapes
│     └── 'GSM8450580_OV_FC_ACT': GeoDataFrame shape: (1676, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1676, 19465)
with coordinate systems:
    ▸ 'GSM8450580_OV_FC_ACT', with elements:
        GSM8450580_OV_FC_ACT_hires_image (Images), GSM8450580_OV_FC_ACT_lowres_image (Images), GSM8450580_OV_FC_ACT (Shapes)
    ▸ 'GSM8450580_OV_FC_ACT_downscaled_hires', with elements:
        GSM8450580_OV_FC_ACT_hires_image (Images), GSM8450580_OV_FC_ACT (Shapes)
    ▸ 'GSM8450580_OV_FC_ACT_downscaled_lowres', with elements:
        GSM8450580_OV_FC_ACT_lowres_image (Images), GSM8450580_OV_FC_ACT (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("C56VXrjloANoiP71")   # 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/C56VXrjloANoiP71

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid C56VXrjloANoiP71
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["C56VXrjloANoiP710000"])[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
ovary
Condition
ovarian cancer
Modality
RNA
Observations
1,676
Tier
bronze
Chemistry
Visium v1
Magnification
other
Resolution
2,000 × 1,974 px
mpp
3.323 µm/px
Size
36 MB
Sample ID
GSM8450580
License
unknown
Published
Oct 15, 2024

Cite this dataset

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

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