Visium

Human brain

GSM8506649

silver Interactive viewer H&E glioblastoma ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8506649_03422_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM8506649_03422_hires_image': DataArray[cyx] (3, 1975, 2000)
│     └── 'GSM8506649_03422_lowres_image': DataArray[cyx] (3, 593, 600)
├── Shapes
│     └── 'GSM8506649_03422': GeoDataFrame shape: (4501, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4501, 18085)
with coordinate systems:
    ▸ 'GSM8506649_03422', with elements:
        GSM8506649_03422_full_image (Images), GSM8506649_03422_hires_image (Images), GSM8506649_03422_lowres_image (Images), GSM8506649_03422 (Shapes)
    ▸ 'GSM8506649_03422_downscaled_hires', with elements:
        GSM8506649_03422_hires_image (Images), GSM8506649_03422 (Shapes)
    ▸ 'GSM8506649_03422_downscaled_lowres', with elements:
        GSM8506649_03422_lowres_image (Images), GSM8506649_03422 (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("uCCYkrPnv88ffdWr")   # 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/uCCYkrPnv88ffdWr

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid uCCYkrPnv88ffdWr

Load with the Python client

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

ds = Catalog().cohort(uids=["uCCYkrPnv88ffdWr0000"])[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

Distinct Myeloid Derived Suppressor Cell Populations in Human Glioblastoma→

2 datasets · replicates

Metadata

Technology: Visium
Organism: human
Tissue: brain
Condition: glioblastoma
Modality: RNA
Observations: 4,501
Tier: silver
Chemistry: Visium CytAssist v2
Resolution: 2,000 × 1,975 px
mpp: 7.858 µm/px
Size: 121 MB
Sample ID: GSM8506649
License: unknown
Published: Jan 23, 2025

Cite this dataset

doi.org/10.1126/science.abm5214 ↗

BibTeX

@article{Jackson_2025,
  title = {Distinct myeloid-derived suppressor cell populations in human glioblastoma},
  volume = {387},
  ISSN = {1095-9203},
  url = {http://dx.doi.org/10.1126/science.abm5214},
  DOI = {10.1126/science.abm5214},
  number = {6731},
  journal = {Science},
  publisher = {American Association for the Advancement of Science (AAAS)},
  author = {Jackson, Christina and Cherry, Christopher and Bom, Sadhana and Dykema, Arbor G. and Wang, Rulin and Thompson, Elizabeth and Zhang, Ming and Li, Runzhe and Ji, Zhicheng and Hou, Wenpin and Zhan, Wentao and Zhang, Hao and Choi, John and Vaghasia, Ajay and Hansen, Landon and Wang, William and Bergsneider, Brandon and Jones, Kate M. and Rodriguez, Fausto and Weingart, Jon and Lucas, Calixto-Hope and Powell, Jonathan and Elisseeff, Jennifer and Yegnasubramanian, Srinivasan and Lim, Michael and Bettegowda, Chetan and Ji, Hongkai and Pardoll, Drew},
  year = {2025},
  month = Jan
}

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