MALDI mass spectrometry imaging
Mouse brain
2019-03-28_09h18m57s
bronze Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'optical_image': DataTree[cyx] (3, 632, 500), (3, 316, 250), (3, 158, 125), (3, 79, 62)
├── Shapes
│ └── 'maldi_spots': GeoDataFrame shape: (92868, 2) (2D shapes)
└── Tables
└── 'table': AnnData (92868, 18)
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("7AGsUt4UcDN1Vw4D") # 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/7AGsUt4UcDN1Vw4D
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 7AGsUt4UcDN1Vw4D Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["7AGsUt4UcDN1Vw4D0000"])[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
- brain
- Modality
- Metabolomics
- Tier
- bronze
- Staining
- H&E
- Resolution
- 500 × 632 px
- mpp
- 25.000 µm/px
- Size
- 6.8 MB
- Sample ID
- 2019-03-28_09h18m57s
- License
- CC BY 4.0
- Published
- Mar 28, 2019
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