Visium

Human brain

GSM7596595

bronze Interactive viewer H&E glioblastoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'GSM7596595_zh1019inf_lowres_image': DataArray[cyx] (3, 561, 600)
├── Shapes
│     └── 'GSM7596595_zh1019inf': GeoDataFrame shape: (1726, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1726, 33538)
with coordinate systems:
    ▸ 'GSM7596595_zh1019inf', with elements:
        GSM7596595_zh1019inf_lowres_image (Images), GSM7596595_zh1019inf (Shapes)
    ▸ 'GSM7596595_zh1019inf_downscaled_hires', with elements:
        GSM7596595_zh1019inf (Shapes)
    ▸ 'GSM7596595_zh1019inf_downscaled_lowres', with elements:
        GSM7596595_zh1019inf_lowres_image (Images), GSM7596595_zh1019inf (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("D7Z7v9UOyohD9S2J0000")
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("D7Z7v9UOyohD9S2J")   # 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 D7Z7v9UOyohD9S2J0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/D7Z7v9UOyohD9S2J

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid D7Z7v9UOyohD9S2J

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Integrative spatial analysis reveals a multi-layered organization of glioblastoma→

19 datasets · replicates

Metadata

Technology: Visium
Organism: human
Tissue: brain
Condition: glioblastoma
Modality: RNA
Observations (spots): 1,726
Tier: bronze
Chemistry: Visium v1
Resolution: 600 × 561 px
mpp: 12.313 µm/px
Size: 16.3 MB
Sample ID: GSM7596595
License: NCBI GEO policy
Published: Feb 18, 2024

Cite this dataset

doi.org/10.1016/j.cell.2024.03.029 ↗

BibTeX

@article{Greenwald_2024,
  title = {Integrative spatial analysis reveals a multi-layered organization of glioblastoma},
  volume = {187},
  ISSN = {0092-8674},
  url = {http://dx.doi.org/10.1016/j.cell.2024.03.029},
  DOI = {10.1016/j.cell.2024.03.029},
  number = {10},
  journal = {Cell},
  publisher = {Elsevier BV},
  author = {Greenwald, Alissa C. and Darnell, Noam Galili and Hoefflin, Rouven and Simkin, Dor and Mount, Christopher W. and Gonzalez Castro, L. Nicolas and Harnik, Yotam and Dumont, Sydney and Hirsch, Dana and Nomura, Masashi and Talpir, Tom and Kedmi, Merav and Goliand, Inna and Medici, Gioele and Laffy, Julie and Li, Baoguo and Mangena, Vamsi and Keren-Shaul, Hadas and Weller, Michael and Addadi, Yoseph and Neidert, Marian C. and Suvà, Mario L. and Tirosh, Itay},
  year = {2024},
  month = May,
  pages = {2485–2501.e26}
}

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