Visium
Human coronary artery
GSM7780297
bronze Interactive viewer H&E atherosclerosis Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7780297_Sample_2_hires_image': DataArray[cyx] (3, 1996, 2000)
│ └── 'GSM7780297_Sample_2_lowres_image': DataArray[cyx] (3, 599, 600)
├── Shapes
│ └── 'GSM7780297_Sample_2': GeoDataFrame shape: (1283, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1283, 17943)
with coordinate systems:
▸ 'GSM7780297_Sample_2', with elements:
GSM7780297_Sample_2_hires_image (Images), GSM7780297_Sample_2_lowres_image (Images), GSM7780297_Sample_2 (Shapes)
▸ 'GSM7780297_Sample_2_downscaled_hires', with elements:
GSM7780297_Sample_2_hires_image (Images), GSM7780297_Sample_2 (Shapes)
▸ 'GSM7780297_Sample_2_downscaled_lowres', with elements:
GSM7780297_Sample_2_lowres_image (Images), GSM7780297_Sample_2 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("SeHuA3WjWFoPJRnF") # 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/SeHuA3WjWFoPJRnF
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid SeHuA3WjWFoPJRnF Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["SeHuA3WjWFoPJRnF0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Clonal proliferation of smooth muscle cell in human atherosclerosis→ 2 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- coronary artery
- Condition
- atherosclerosis
- Modality
- RNA
- Observations
- 1,283
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,996 px
- mpp
- 3.557 µm/px
- Size
- 3.3 MB
- Sample ID
- GSM7780297
- License
- unknown
- Published
- Dec 4, 2023
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB