Visium

Human breast

GSM6433613

bronze Interactive viewer H&E triple-negative breast carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'GSM6433613_395A_hires_image': DataArray[cyx] (3, 1968, 2000)
├── Shapes
│     └── 'GSM6433613_395A': GeoDataFrame shape: (1868, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1868, 36601)
with coordinate systems:
    ▸ 'GSM6433613_395A', with elements:
        GSM6433613_395A_hires_image (Images), GSM6433613_395A (Shapes)
    ▸ 'GSM6433613_395A_downscaled_hires', with elements:
        GSM6433613_395A_hires_image (Images), GSM6433613_395A (Shapes)
    ▸ 'GSM6433613_395A_downscaled_lowres', with elements:
        GSM6433613_395A (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("XG9btcMybp1iFRGx0000")
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("XG9btcMybp1iFRGx")   # 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 XG9btcMybp1iFRGx0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/XG9btcMybp1iFRGx

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XG9btcMybp1iFRGx

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Spatial transcriptomics of triple negative breast cancer→

43 datasets · other

Metadata

Technology: Visium
Organism: human
Tissue: breast
Condition: triple-negative breast carcinoma
Modality: RNA
Observations (spots): 1,868
Tier: bronze
Chemistry: Visium v1
Resolution: 2,000 × 1,968 px
mpp: 3.638 µm/px
Size: 30.1 MB
Sample ID: GSM6433613
License: NCBI GEO policy
Published: Nov 2, 2022

Cite this dataset

doi.org/10.1158/0008-5472.can-22-2682 ↗

BibTeX

@article{Bassiouni_2022,
  title = {Spatial Transcriptomic Analysis of a Diverse Patient Cohort Reveals a Conserved Architecture in Triple-Negative Breast Cancer},
  volume = {83},
  ISSN = {1538-7445},
  url = {http://dx.doi.org/10.1158/0008-5472.can-22-2682},
  DOI = {10.1158/0008-5472.can-22-2682},
  number = {1},
  journal = {Cancer Research},
  publisher = {American Association for Cancer Research (AACR)},
  author = {Bassiouni, Rania and Idowu, Michael O. and Gibbs, Lee D. and Robila, Valentina and Grizzard, Pamela J. and Webb, Michelle G. and Song, Jiarong and Noriega, Ashley and Craig, David W. and Carpten, John D.},
  year = {2022},
  month = Oct,
  pages = {34–48}
}

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