MALDI mass spectrometry imaging
Mouse colon
2025-01-17_11h10m04s
bronze Interactive viewer H&E malignant colon neoplasm ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'optical_image': DataTree[cyx] (3, 10597, 6342), (3, 5298, 3171), (3, 2649, 1585), (3, 1324, 792)
├── Shapes
│ └── 'maldi_spots': GeoDataFrame shape: (51436, 2) (2D shapes)
└── Tables
└── 'table': AnnData (51436, 110)
with coordinate systems:
▸ 'global', with elements:
optical_image (Images), maldi_spots (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("S4OYB6V39ZTo4Nha0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("S4OYB6V39ZTo4Nha") # stem uid: Lamin resolves it to the 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download S4OYB6V39ZTo4Nha0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/S4OYB6V39ZTo4Nha
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid S4OYB6V39ZTo4NhaLicense: CC BY 4.0
Metadata
- Technology
- MALDI mass spectrometry imaging
- Organism
- mouse
- Tissue
- colon
- Condition
- malignant colon neoplasm
- Modality
- Metabolomics
- Observations
- 51,436
- Tier
- bronze
- Resolution
- 6,342 × 10,597 px
- mpp
- 25.000 µm/px
- Size
- 186 MB
- Sample ID
- 2025-01-17_11h10m04s
- License
- CC BY 4.0
- Published
- Sep 25, 2026
Cite this dataset
doi.org/10.1126/science.adw8520 ↗ BibTeX
@article{metaspace:2025-01-17_11h10m04s,
doi = {10.1126/science.adw8520},
title = {2025-01-17_11h10m04s},
year = {2026}
}Source: metaspace2020.org ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB