Visium

Human liver

GSM7697869

bronze Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM7697869_C73B1_hires_image': DataArray[cyx] (4, 2000, 1963)
│     └── 'GSM7697869_C73B1_lowres_image': DataArray[cyx] (4, 600, 589)
├── Shapes
│     └── 'GSM7697869_C73B1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4992, 36601)
with coordinate systems:
    ▸ 'GSM7697869_C73B1', with elements:
        GSM7697869_C73B1_hires_image (Images), GSM7697869_C73B1_lowres_image (Images), GSM7697869_C73B1 (Shapes)
    ▸ 'GSM7697869_C73B1_downscaled_hires', with elements:
        GSM7697869_C73B1_hires_image (Images), GSM7697869_C73B1 (Shapes)
    ▸ 'GSM7697869_C73B1_downscaled_lowres', with elements:
        GSM7697869_C73B1_lowres_image (Images), GSM7697869_C73B1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("0Er4Pnvi60YSgBFW0001")
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("0Er4Pnvi60YSgBFW")   # 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 0Er4Pnvi60YSgBFW0001 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/0Er4Pnvi60YSgBFW

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 0Er4Pnvi60YSgBFW

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Single-cell and spatial transcriptomics characterisation of the immunological landscape in the healthy and PSC human liver→

4 datasets · other

Metadata

Technology: Visium
Organism: human
Tissue: liver
Modality: RNA
Observations (spots): 4,992
Tier: bronze
Chemistry: Visium v1
Size: 31.7 MB
Sample ID: GSM7697869
License: NCBI GEO policy
Published: Sep 26, 2023

Cite this dataset

doi.org/10.1016/j.jhep.2023.12.023 ↗

BibTeX

@article{Andrews_2024,
  title = {Single-cell, single-nucleus, and spatial transcriptomics characterization of the immunological landscape in the healthy and PSC human liver},
  volume = {80},
  ISSN = {0168-8278},
  url = {http://dx.doi.org/10.1016/j.jhep.2023.12.023},
  DOI = {10.1016/j.jhep.2023.12.023},
  number = {5},
  journal = {Journal of Hepatology},
  publisher = {Elsevier BV},
  author = {Andrews, Tallulah S. and Nakib, Diana and Perciani, Catia T. and Ma, Xue Zhong and Liu, Lewis and Winter, Erin and Camat, Damra and Chung, Sai W. and Lumanto, Patricia and Manuel, Justin and Mangroo, Shantel and Hansen, Bettina and Arpinder, Bal and Thoeni, Cornelia and Sayed, Blayne and Feld, Jordan and Gehring, Adam and Gulamhusein, Aliya and Hirschfield, Gideon M. and Ricciuto, Amanda and Bader, Gary D. and McGilvray, Ian D. and MacParland, Sonya},
  year = {2024},
  month = May,
  pages = {730–743}
}

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