Visium

Human liver

GSM7850822

bronze Interactive viewer H&E hepatocellular carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM7850822_CHC20_hires_image': DataArray[cyx] (3, 2000, 1913)
│     └── 'GSM7850822_CHC20_lowres_image': DataArray[cyx] (3, 600, 574)
├── Shapes
│     └── 'GSM7850822_CHC20': GeoDataFrame shape: (2261, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2261, 36601)
with coordinate systems:
    ▸ 'GSM7850822_CHC20', with elements:
        GSM7850822_CHC20_hires_image (Images), GSM7850822_CHC20_lowres_image (Images), GSM7850822_CHC20 (Shapes)
    ▸ 'GSM7850822_CHC20_downscaled_hires', with elements:
        GSM7850822_CHC20_hires_image (Images), GSM7850822_CHC20 (Shapes)
    ▸ 'GSM7850822_CHC20_downscaled_lowres', with elements:
        GSM7850822_CHC20_lowres_image (Images), GSM7850822_CHC20 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("3BU67ZvZsUOWpK8P0000")
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("3BU67ZvZsUOWpK8P")   # 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 3BU67ZvZsUOWpK8P0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/3BU67ZvZsUOWpK8P

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 3BU67ZvZsUOWpK8P

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Identification of TREM1+CD163+ myeloid cells as a deleterious immune subset in HCC [Spatial Transcriptomics]→

2 datasets · replicates

Metadata

Technology: Visium
Organism: human
Tissue: liver
Condition: hepatocellular carcinoma
Modality: RNA
Observations (spots): 2,261
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 1,913 × 2,000 px
mpp: 4.790 µm/px
Size: 48.5 MB
Sample ID: GSM7850822
License: NCBI GEO policy
Published: Feb 4, 2024

Cite this dataset

doi.org/10.1016/j.celrep.2024.113773 ↗

BibTeX

@article{Giraud_2024,
  title = {THBS1+ myeloid cells expand in SLD hepatocellular carcinoma and contribute to immunosuppression and unfavorable prognosis through TREM1},
  volume = {43},
  ISSN = {2211-1247},
  url = {http://dx.doi.org/10.1016/j.celrep.2024.113773},
  DOI = {10.1016/j.celrep.2024.113773},
  number = {2},
  journal = {Cell Reports},
  publisher = {Elsevier BV},
  author = {Giraud, Julie and Chalopin, Domitille and Ramel, Eloïse and Boyer, Thomas and Zouine, Atika and Derieppe, Marie-Alix and Larmonier, Nicolas and Adotevi, Olivier and Le Bail, Brigitte and Blanc, Jean-Frédéric and Laurent, Christophe and Chiche, Laurence and Derive, Marc and Nikolski, Macha and Saleh, Maya},
  year = {2024},
  month = Feb,
  pages = {113773}
}

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