Visium
Mouse heart
GSM6613078
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_hires_image': DataArray[cyx] (3, 1804, 2000)
│ └── 'GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_lowres_image': DataArray[cyx] (3, 541, 600)
├── Shapes
│ └── 'GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4': GeoDataFrame shape: (3057, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3057, 32285)
with coordinate systems:
▸ 'GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4', with elements:
GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_hires_image (Images), GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_lowres_image (Images), GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4 (Shapes)
▸ 'GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_downscaled_hires', with elements:
GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_hires_image (Images), GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4 (Shapes)
▸ 'GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_downscaled_lowres', with elements:
GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4_lowres_image (Images), GSM6613078_V_1Hr_4Hr_d3_Np_4_V_1Hr_4Hr_d3_Np_4 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("PTtMrpruW58Nk3ay") # 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/PTtMrpruW58Nk3ay
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid PTtMrpruW58Nk3ay Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["PTtMrpruW58Nk3ay0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Single Cell Spatial Transcriptomics Redefines the Borderzone induced by Myocardial Infarction and Mechanical Injury→ 14 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- heart
- Modality
- RNA
- Observations
- 3,057
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,804 px
- mpp
- 3.333 µm/px
- Size
- 29 MB
- Sample ID
- GSM6613078
- License
- unknown
- Published
- Oct 3, 2022
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB