Visium
Mouse liver
GSM6859073
silver H&E colorectal cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6859073_Sample22_hires_image': DataArray[cyx] (3, 2000, 1965)
│ └── 'GSM6859073_Sample22_lowres_image': DataArray[cyx] (3, 600, 590)
├── Shapes
│ └── 'GSM6859073_Sample22': GeoDataFrame shape: (1544, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1544, 32287)
with coordinate systems:
▸ 'GSM6859073_Sample22', with elements:
GSM6859073_Sample22_hires_image (Images), GSM6859073_Sample22_lowres_image (Images), GSM6859073_Sample22 (Shapes)
▸ 'GSM6859073_Sample22_downscaled_hires', with elements:
GSM6859073_Sample22_hires_image (Images), GSM6859073_Sample22 (Shapes)
▸ 'GSM6859073_Sample22_downscaled_lowres', with elements:
GSM6859073_Sample22_lowres_image (Images), GSM6859073_Sample22 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("9H7Tdq9FPWlGUeLL") # 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/9H7Tdq9FPWlGUeLL
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 9H7Tdq9FPWlGUeLL Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["9H7Tdq9FPWlGUeLL0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
In vivo macrophage engineering reshapes the tumor microenvironment leading to eradication of liver metastases [Visium]→ 8 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- liver
- Condition
- colorectal cancer
- Modality
- RNA
- Observations
- 1,544
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 1,965 × 2,000 px
- mpp
- 3.544 µm/px
- Size
- 25 MB
- Sample ID
- GSM6859073
- License
- unknown
- Published
- Sep 27, 2023
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB