Visium

Mouse skin of body

GSM7461404

bronze Interactive viewer H&E skin squamous cell carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM7461404_SFE65_NP137_T1_hires_image': DataArray[cyx] (3, 2000, 1979)
│     └── 'GSM7461404_SFE65_NP137_T1_lowres_image': DataArray[cyx] (3, 600, 594)
├── Shapes
│     └── 'GSM7461404_SFE65_NP137_T1': GeoDataFrame shape: (1166, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1166, 19465)
with coordinate systems:
    ▸ 'GSM7461404_SFE65_NP137_T1', with elements:
        GSM7461404_SFE65_NP137_T1_hires_image (Images), GSM7461404_SFE65_NP137_T1_lowres_image (Images), GSM7461404_SFE65_NP137_T1 (Shapes)
    ▸ 'GSM7461404_SFE65_NP137_T1_downscaled_hires', with elements:
        GSM7461404_SFE65_NP137_T1_hires_image (Images), GSM7461404_SFE65_NP137_T1 (Shapes)
    ▸ 'GSM7461404_SFE65_NP137_T1_downscaled_lowres', with elements:
        GSM7461404_SFE65_NP137_T1_lowres_image (Images), GSM7461404_SFE65_NP137_T1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("xDub0keSBBJ0mwWu0000")
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("xDub0keSBBJ0mwWu")   # 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 xDub0keSBBJ0mwWu0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/xDub0keSBBJ0mwWu

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid xDub0keSBBJ0mwWu

Install (Python 3.12+) Docs →

License: NCBI GEO policy

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

Pharmacological targeting Netrin-1 inhibits EMT in cancer [Visium]→

2 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: skin of body
Condition: skin squamous cell carcinoma
Modality: RNA
Observations (spots): 1,166
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 1,979 × 2,000 px
mpp: 3.305 µm/px
Size: 22.1 MB
Sample ID: GSM7461404
License: NCBI GEO policy
Published: Jun 13, 2023

Cite this dataset

doi.org/10.1038/s41586-023-06372-2 ↗

BibTeX

@article{Lengrand_2023,
  title = {Pharmacological targeting of netrin-1 inhibits EMT in cancer},
  volume = {620},
  ISSN = {1476-4687},
  url = {http://dx.doi.org/10.1038/s41586-023-06372-2},
  DOI = {10.1038/s41586-023-06372-2},
  number = {7973},
  journal = {Nature},
  publisher = {Springer Science and Business Media LLC},
  author = {Lengrand, Justine and Pastushenko, Ievgenia and Vanuytven, Sebastiaan and Song, Yura and Venet, David and Sarate, Rahul M. and Bellina, Melanie and Moers, Virginie and Boinet, Alice and Sifrim, Alejandro and Rama, Nicolas and Ducarouge, Benjamin and Van Herck, Jens and Dubois, Christine and Scozzaro, Samuel and Lemaire, Sophie and Gieskes, Sarah and Bonni, Sophie and Collin, Amandine and Braissand, Nicolas and Allard, Justine and Zindy, Egor and Decaestecker, Christine and Sotiriou, Christos and Salmon, Isabelle and Mehlen, Patrick and Voet, Thierry and Bernet, Agnès and Blanpain, Cédric},
  year = {2023},
  month = Aug,
  pages = {402–408}
}

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB