Visium

Human brain

NCBI632

silver Interactive viewer H&E ependymoma ✓ Verified publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'NCBI632_full_image': DataTree[cyx] (3, 10154, 9911), (3, 5077, 4955), (3, 2538, 2477), (3, 1269, 1238)
├── Shapes
│     └── 'NCBI632_spots': GeoDataFrame shape: (2743, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2743, 36601)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI632_full_image (Images), NCBI632_spots (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("JynFCR8DjyR2DwB20000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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("JynFCR8DjyR2DwB2")   # 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download JynFCR8DjyR2DwB20000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/JynFCR8DjyR2DwB2

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid JynFCR8DjyR2DwB2

Install (Python 3.12+) Docs →

License: CC BY-NC-SA 4.0 (noncommercial)

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Part of collection

Spatial transcriptomics reveal unnresolved wound repair as potential driver of PFA Ependymoma progression→

14 datasets · replicates

Metadata

Technology: Visium
Organism: human
Tissue: brain
Condition: ependymoma
Modality: RNA
Observations (spots): 2,743
Tier: silver
Chemistry: Visium v1
Resolution: 9,911 × 10,154 px
mpp: 0.799 µm/px
Size: 284 MB
Sample ID: NCBI632
License: CC BY-NC-SA 4.0 NonCommercial
Published: Oct 13, 2022

Cite this dataset

doi.org/10.1093/neuonc/noac079.165 ↗

BibTeX

@article{Donson_2022,
  title = {EPEN-29. Spatial transcriptomic analysis of ependymoma implicates unresolved wound healing as a driver of tumor progression},
  volume = {24},
  ISSN = {1523-5866},
  url = {http://dx.doi.org/10.1093/neuonc/noac079.165},
  DOI = {10.1093/neuonc/noac079.165},
  number = {Supplement_1},
  journal = {Neuro-Oncology},
  publisher = {Oxford University Press (OUP)},
  author = {Donson, Andrew and Fu, Rui and Norris, gregory and Willard, Nicholas and Griesinger, Andrea and Riemondy, Kent and Amani, Vladimir and Grimaldo, Enrique and Harris, Faith and Hankinson, Todd and Mitra, Siddhartha and Ritzmann, timothy and Grundy, Richard and Foreman, Nicholas},
  year = {2022},
  month = June,
  pages = {i45–i45}
}

Source: academic.oup.com ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB