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MALDI mass spectrometry imaging

Human kidney

2023-01-17_22h30m56s

bronze Interactive viewer H&E cancer ✓ Verified publication
Human kidney preview
print(sdata)
SpatialData object
├── Images
│     └── 'optical_image': DataTree[cyx] (3, 2053, 3094), (3, 1026, 1547), (3, 513, 773), (3, 256, 386)
├── Shapes
│     └── 'maldi_spots': GeoDataFrame shape: (403263, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (403263, 2)
with coordinate systems:
    ▸ 'global', with elements:
        optical_image (Images), maldi_spots (Shapes)
Python · sddb client
from sddb import Catalog

ds = Catalog().dataset("D4PmvrhoPZEkaQdt0000")
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("D4PmvrhoPZEkaQdt")   # 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 D4PmvrhoPZEkaQdt0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/D4PmvrhoPZEkaQdt

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid D4PmvrhoPZEkaQdt

License: CC BY 4.0

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Metadata

Technology
MALDI mass spectrometry imaging
Organism
human
Tissue
kidney
Condition
cancer
Modality
Metabolomics
Observations
403,263
Tier
bronze
Resolution
3,094 × 2,053 px
mpp
40.000 µm/px
Size
15.9 MB
Sample ID
2023-01-17_22h30m56s
License
CC BY 4.0
Published
Jan 4, 2024

Cite this dataset

doi.org/10.1038/s41598-023-50957-w ↗
BibTeX
@article{metaspace:2023-01-17_22h30m56s,
  doi = {10.1038/s41598-023-50957-w},
  title = {2023-01-17_22h30m56s},
  year = {2024}
}

Source: metaspace2020.org ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB