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Visium

Mouse stomach

GSM5643203

bronze Interactive viewer H&E gastric cancer Provisional
Mouse stomach preview
print(sdata) 
SpatialData object
├── Images
│     └── 'GSM5643203_hires_image': DataArray[cyx] (3, 2000, 1818)
├── Shapes
│     └── 'GSM5643203': GeoDataFrame shape: (2429, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2429, 31054)
with coordinate systems:
    ▸ 'GSM5643203', with elements:
        GSM5643203_hires_image (Images), GSM5643203 (Shapes)
    ▸ 'GSM5643203_downscaled_hires', with elements:
        GSM5643203_hires_image (Images), GSM5643203 (Shapes)
    ▸ 'GSM5643203_downscaled_lowres', with elements:
        GSM5643203 (Shapes)
Install (Python 3.12+) Docs →
Python · sddb client 
from sddb import Catalog

ds = Catalog().dataset("5l4rEUB1UkO0lPCj0000")
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("5l4rEUB1UkO0lPCj")   # 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 5l4rEUB1UkO0lPCj0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/5l4rEUB1UkO0lPCj

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 5l4rEUB1UkO0lPCj
Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Metadata

Technology
Visium
Organism
mouse
Tissue
stomach
Condition
gastric cancer
Modality
RNA
Observations (spots)
2,429
Tier
bronze
Chemistry
Visium v1
Magnification
other
Resolution
1,818 × 2,000 px
mpp
4.054 µm/px
Size
41.2 MB
Sample ID
GSM5643203
License
NCBI GEO policy
Published
Oct 21, 2021

Cite this dataset

doi.org/10.1111/cas.15244 ↗
BibTeX 
@article{Yamasaki_2022,
  title = {MEK inhibition suppresses metastatic progression of
                    <i>KRAS</i>
                    ‐mutated gastric cancer},
  volume = {113},
  ISSN = {1349-7006},
  url = {http://dx.doi.org/10.1111/cas.15244},
  DOI = {10.1111/cas.15244},
  number = {3},
  journal = {Cancer Science},
  publisher = {Wiley},
  author = {Yamasaki, Juntaro and Hirata, Yuki and Otsuki, Yuji and Suina, Kentaro and Saito, Yoshiyuki and Masuda, Kenta and Okazaki, Shogo and Ishimoto, Takatsugu and Saya, Hideyuki and Nagano, Osamu},
  year = {2022},
  month = Jan,
  pages = {916–925}
}

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