Visium
Human peritoneum
GSM8279112
bronze Interactive viewer H&E desmoplastic small round cell tumor Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8279112_GR11_site1_hires_image': DataArray[cyx] (3, 2000, 1911)
│ └── 'GSM8279112_GR11_site1_lowres_image': DataArray[cyx] (3, 600, 573)
├── Shapes
│ └── 'GSM8279112_GR11_site1': GeoDataFrame shape: (3697, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3697, 17943)
with coordinate systems:
▸ 'GSM8279112_GR11_site1', with elements:
GSM8279112_GR11_site1_hires_image (Images), GSM8279112_GR11_site1_lowres_image (Images), GSM8279112_GR11_site1 (Shapes)
▸ 'GSM8279112_GR11_site1_downscaled_hires', with elements:
GSM8279112_GR11_site1_hires_image (Images), GSM8279112_GR11_site1 (Shapes)
▸ 'GSM8279112_GR11_site1_downscaled_lowres', with elements:
GSM8279112_GR11_site1_lowres_image (Images), GSM8279112_GR11_site1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("nJheLNll9sJIOqDa0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) 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("nJheLNll9sJIOqDa") # 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download nJheLNll9sJIOqDa0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/nJheLNll9sJIOqDa
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nJheLNll9sJIOqDaLicense: NCBI GEO policy
Part of collection
Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in Desmoplastic Small Round Cell Tumors [Visium: Spatial transcriptomics]→ 6 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- peritoneum
- Condition
- desmoplastic small round cell tumor
- Modality
- RNA
- Observations (spots)
- 3,697
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,911 × 2,000 px
- mpp
- 3.642 µm/px
- Size
- 66.6 MB
- Sample ID
- GSM8279112
- License
- NCBI GEO policy
- Published
- Apr 15, 2024
Cite this dataset
doi.org/10.1016/j.xcrm.2024.101582 ↗ BibTeX
@article{Henon_2024,
title = {Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in DSRCTs},
volume = {5},
ISSN = {2666-3791},
url = {http://dx.doi.org/10.1016/j.xcrm.2024.101582},
DOI = {10.1016/j.xcrm.2024.101582},
number = {6},
journal = {Cell Reports Medicine},
publisher = {Elsevier BV},
author = {Henon, Clémence and Vibert, Julien and Eychenne, Thomas and Gruel, Nadège and Colmet-Daage, Léo and Ngo, Carine and Garrido, Marlène and Dorvault, Nicolas and Marques Da Costa, Maria Eugenia and Marty, Virginie and Signolle, Nicolas and Marchais, Antonin and Herbel, Noé and Kawai-Kawachi, Asuka and Lenormand, Madison and Astier, Clémence and Chabanon, Roman and Verret, Benjamin and Bahleda, Rastislav and Le Cesne, Axel and Mechta-Grigoriou, Fatima and Faron, Matthieu and Honoré, Charles and Delattre, Olivier and Waterfall, Joshua J. and Watson, Sarah and Postel-Vinay, Sophie},
year = {2024},
month = June,
pages = {101582}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB