Visium HD

Human caudate lobe of liver

GSM9324329

silver Interactive viewer H&E liver disorder ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_hires_image': DataArray[cyx] (3, 4651, 6000)
│     └── 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_lowres_image': DataArray[cyx] (3, 465, 600)
├── Shapes
│     ├── 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um': GeoDataFrame shape: (7437879, 1) (2D shapes)
│     ├── 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um': GeoDataFrame shape: (466284, 1) (2D shapes)
│     ├── 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um': GeoDataFrame shape: (116978, 1) (2D shapes)
│     └── 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce': GeoDataFrame shape: (116978, 2) (2D shapes)
└── Tables
      ├── 'square_002um': AnnData (7437879, 18085)
      ├── 'square_008um': AnnData (466284, 18085)
      └── 'square_016um': AnnData (116978, 18085)
with coordinate systems:
    ▸ 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix', with elements:
        GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_hires_image (Images), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_lowres_image (Images), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce (Shapes)
    ▸ 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_downscaled_hires', with elements:
        GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_hires_image (Images), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce (Shapes)
    ▸ 'GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_downscaled_lowres', with elements:
        GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_lowres_image (Images), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um (Shapes), GSM9324329_C95-3_A1_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Fvj5OQtkecvGKkT5")   # 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/Fvj5OQtkecvGKkT5

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Fvj5OQtkecvGKkT5

Load with the Python client

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

ds = Catalog().cohort(uids=["Fvj5OQtkecvGKkT50000"])[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

High-resolution spatial transcriptomics of human liver with VisiumHD→

3 datasets · other

Metadata

Technology: Visium HD
Organism: human
Tissue: caudate lobe of liver
Condition: liver disorder
Modality: RNA
Observations: 466,284
Tier: silver
Resolution: 6,000 × 4,651 px
mpp: 1.785 µm/px
Size: 926 MB
Sample ID: GSM9324329
License: NCBI GEO policy
Published: Apr 17, 2026

Cite this dataset

doi.org/10.1038/s41597-026-07597-2 ↗

BibTeX

@article{Hasan_2026,
  title = {High-resolution spatial transcriptomics of adult and pediatric human liver with Visium HD},
  ISSN = {2052-4463},
  url = {http://dx.doi.org/10.1038/s41597-026-07597-2},
  DOI = {10.1038/s41597-026-07597-2},
  journal = {Scientific Data},
  publisher = {Springer Science and Business Media LLC},
  author = {Hasan, Faizan and Edgar, Rachel D. and Atif, Jawairia and Nakib, Diana and Thoeni, Cornelia and Ricciuto, Amanda and Sayed, Blayne A. and McGilvray, Ian and Bader, Gary D. and MacParland, Sonya A.},
  year = {2026},
  month = June
}

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