Visium

Human liver

GSM8657786

silver Interactive viewer H&E hepatoblastoma ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8657786_H1225_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM8657786_H1225_hires_image': DataArray[cyx] (3, 2000, 2000)
│     └── 'GSM8657786_H1225_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│     └── 'GSM8657786_H1225': GeoDataFrame shape: (4563, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4563, 18085)
with coordinate systems:
    ▸ 'GSM8657786_H1225', with elements:
        GSM8657786_H1225_full_image (Images), GSM8657786_H1225_hires_image (Images), GSM8657786_H1225_lowres_image (Images), GSM8657786_H1225 (Shapes)
    ▸ 'GSM8657786_H1225_downscaled_hires', with elements:
        GSM8657786_H1225_hires_image (Images), GSM8657786_H1225 (Shapes)
    ▸ 'GSM8657786_H1225_downscaled_lowres', with elements:
        GSM8657786_H1225_lowres_image (Images), GSM8657786_H1225 (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("zptMJX9rGZlGLmOx")   # 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

Load from the CLI

# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/zptMJX9rGZlGLmOx

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid zptMJX9rGZlGLmOx

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["zptMJX9rGZlGLmOx0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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

Part of collection

Multiomic analysis uncovers a continuous spectrum of differentiation and Wnt-MDK-driven immune evasion in hepatoblastoma [Spatial Transcriptomics]→

22 datasets · other

Metadata

Technology: Visium
Organism: human
Tissue: liver
Condition: hepatoblastoma
Modality: RNA
Observations: 4,563
Tier: silver
Chemistry: Visium CytAssist v2
Resolution: 3,000 × 3,000 px
mpp: 3.700 µm/px
Size: 74 MB
Sample ID: GSM8657786
License: NCBI GEO policy
Published: Feb 7, 2025

Cite this dataset

doi.org/10.1016/j.jhep.2025.01.031 ↗

BibTeX

@article{M_nter_2025,
  title = {Multiomic analysis uncovers a continuous spectrum of differentiation and Wnt-MDK-driven immune evasion in hepatoblastoma},
  volume = {83},
  ISSN = {0168-8278},
  url = {http://dx.doi.org/10.1016/j.jhep.2025.01.031},
  DOI = {10.1016/j.jhep.2025.01.031},
  number = {2},
  journal = {Journal of Hepatology},
  publisher = {Elsevier BV},
  author = {Münter, Daniel and de Faria, Flavia W. and Richter, Mathis and Aranda-Pardos, Irene and Hotfilder, Marc and Walter, Carolin and Paga, Enya and Inserte, Clara and Albert, Thomas K. and Roy, Rajanya and Rahman, Shariyah and Riedel, Nicole C. and Müller, Volker and Pascher, Andreas and Wiebe, Karsten and Schmid, Irene and Vokuhl, Christian and Winkler, Beate and Jüttner, Eva and Vieth, Simon and Mücke, Urs and Kluiver, Thomas A. and Peng, Weng Chuan and Rossig, Claudia and Schlué, Jerome and Madadi-Sanjani, Omid and Sandmann, Sarah and Hartmann, Wolfgang and A-Gonzalez, Noelia and Soehnlein, Oliver and Kerl, Kornelius},
  year = {2025},
  month = Aug,
  pages = {367–382}
}

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