Visium
Human liver
GSM7850823
bronze Interactive viewer H&E hepatocellular carcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7850823_CHC23_hires_image': DataArray[cyx] (3, 2000, 1965)
│ └── 'GSM7850823_CHC23_lowres_image': DataArray[cyx] (3, 600, 590)
├── Shapes
│ └── 'GSM7850823_CHC23': GeoDataFrame shape: (1987, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1987, 36601)
with coordinate systems:
▸ 'GSM7850823_CHC23', with elements:
GSM7850823_CHC23_hires_image (Images), GSM7850823_CHC23_lowres_image (Images), GSM7850823_CHC23 (Shapes)
▸ 'GSM7850823_CHC23_downscaled_hires', with elements:
GSM7850823_CHC23_hires_image (Images), GSM7850823_CHC23 (Shapes)
▸ 'GSM7850823_CHC23_downscaled_lowres', with elements:
GSM7850823_CHC23_lowres_image (Images), GSM7850823_CHC23 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("m2hTEulwlT4ZXHEK") # 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/m2hTEulwlT4ZXHEK
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid m2hTEulwlT4ZXHEK Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["m2hTEulwlT4ZXHEK0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Identification of TREM1+CD163+ myeloid cells as a deleterious immune subset in HCC [Spatial Transcriptomics]→ 2 datasets · replicates
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- liver
- Condition
- hepatocellular carcinoma
- Modality
- RNA
- Observations
- 1,987
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,965 × 2,000 px
- mpp
- 4.966 µm/px
- Size
- 37 MB
- Sample ID
- GSM7850823
- License
- unknown
- Published
- Feb 4, 2024
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB