MALDI mass spectrometry imaging
Mouse kidney
2024-03-14_19h23m36s
bronze Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'optical_image': DataTree[cyx] (3, 5970, 5736), (3, 2985, 2868), (3, 1492, 1434), (3, 746, 717)
├── Shapes
│ └── 'maldi_spots': GeoDataFrame shape: (15867, 2) (2D shapes)
└── Tables
└── 'table': AnnData (15867, 15)
with coordinate systems:
▸ 'global', with elements:
optical_image (Images), maldi_spots (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("ukWHkbKwtDuX2KGN") # 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/ukWHkbKwtDuX2KGN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ukWHkbKwtDuX2KGN Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ukWHkbKwtDuX2KGN0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- MALDI mass spectrometry imaging
- Organism
- mouse
- Tissue
- kidney
- Modality
- Metabolomics
- Tier
- bronze
- Resolution
- 5,736 × 5,970 px
- mpp
- 50.000 µm/px
- Size
- 63 MB
- Sample ID
- 2024-03-14_19h23m36s
- License
- CC BY 4.0
- Published
- Mar 14, 2024
Cite this dataset
No linked publication found — please cite the data source: metaspace2020.org ↗.
Source: metaspace2020.org ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB