Visium
Mouse heart
GSM5355663
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM5355663_WT_Sham_full_image': DataTree[cyx] (3, 3674, 3410), (3, 1837, 1705), (3, 918, 852), (3, 459, 426), (3, 229, 213)
│ └── 'GSM5355663_WT_Sham_hires_image': DataArray[cyx] (3, 2000, 1856)
├── Shapes
│ └── 'GSM5355663_WT_Sham': GeoDataFrame shape: (1689, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1689, 32285)
with coordinate systems:
▸ 'GSM5355663_WT_Sham', with elements:
GSM5355663_WT_Sham_full_image (Images), GSM5355663_WT_Sham_hires_image (Images), GSM5355663_WT_Sham (Shapes)
▸ 'GSM5355663_WT_Sham_downscaled_hires', with elements:
GSM5355663_WT_Sham_hires_image (Images), GSM5355663_WT_Sham (Shapes)
▸ 'GSM5355663_WT_Sham_downscaled_lowres', with elements:
GSM5355663_WT_Sham (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("XWfGchKkcsPEPnxA") # 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/XWfGchKkcsPEPnxA
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XWfGchKkcsPEPnxA Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["XWfGchKkcsPEPnxA0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatiotemporal transcriptome analysis reveals critical roles for mechano-sensing genes at the border zone in remodeling after myocardial infarction→ 14 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- heart
- Modality
- RNA
- Observations
- 1,689
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 3,410 × 3,674 px
- mpp
- 1.968 µm/px
- Size
- 43 MB
- Sample ID
- GSM5355663
- License
- unknown
- Published
- Jul 25, 2022
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB