Visium

Human oral cavity

GSM6339635

bronze Interactive viewer H&E oral cavity squamous cell carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'GSM6339635_s5_hires_image': DataArray[cyx] (3, 2000, 1965)
├── Shapes
│     └── 'GSM6339635_s5': GeoDataFrame shape: (1678, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1678, 36601)
with coordinate systems:
    ▸ 'GSM6339635_s5', with elements:
        GSM6339635_s5_hires_image (Images), GSM6339635_s5 (Shapes)
    ▸ 'GSM6339635_s5_downscaled_hires', with elements:
        GSM6339635_s5_hires_image (Images), GSM6339635_s5 (Shapes)
    ▸ 'GSM6339635_s5_downscaled_lowres', with elements:
        GSM6339635_s5 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("SoprMimMiIsv4YTO0000")
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("SoprMimMiIsv4YTO")   # 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 SoprMimMiIsv4YTO0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/SoprMimMiIsv4YTO

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid SoprMimMiIsv4YTO

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response→

12 datasets · time course

Metadata

Technology: Visium
Organism: human
Tissue: oral cavity
Condition: oral cavity squamous cell carcinoma
Modality: RNA
Observations (spots): 1,678
Tier: bronze
Chemistry: Visium v1
Resolution: 1,965 × 2,000 px
mpp: 3.356 µm/px
Size: 22.9 MB
Sample ID: GSM6339635
License: NCBI GEO policy
Published: Jun 25, 2023

Cite this dataset

doi.org/10.1038/s41467-023-40271-4 ↗

BibTeX

@article{Arora_2023,
  title = {Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-40271-4},
  DOI = {10.1038/s41467-023-40271-4},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Arora, Rohit and Cao, Christian and Kumar, Mehul and Sinha, Sarthak and Chanda, Ayan and McNeil, Reid and Samuel, Divya and Arora, Rahul K. and Matthews, T. Wayne and Chandarana, Shamir and Hart, Robert and Dort, Joseph C. and Biernaskie, Jeff and Neri, Paola and Hyrcza, Martin D. and Bose, Pinaki},
  year = {2023},
  month = Aug
}

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