Visium
Human skin of body
GSM7657719
bronze Interactive viewer H&E melanoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7657719_SC2200094_hires_image': DataArray[cyx] (3, 2000, 1986)
│ └── 'GSM7657719_SC2200094_lowres_image': DataArray[cyx] (3, 600, 596)
├── Shapes
│ └── 'GSM7657719_SC2200094': GeoDataFrame shape: (4991, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4991, 68886)
with coordinate systems:
▸ 'GSM7657719_SC2200094', with elements:
GSM7657719_SC2200094_hires_image (Images), GSM7657719_SC2200094_lowres_image (Images), GSM7657719_SC2200094 (Shapes)
▸ 'GSM7657719_SC2200094_downscaled_hires', with elements:
GSM7657719_SC2200094_hires_image (Images), GSM7657719_SC2200094 (Shapes)
▸ 'GSM7657719_SC2200094_downscaled_lowres', with elements:
GSM7657719_SC2200094_lowres_image (Images), GSM7657719_SC2200094 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("qlp8L12FqN0t722M0000")
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("qlp8L12FqN0t722M") # 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 qlp8L12FqN0t722M0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/qlp8L12FqN0t722M
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid qlp8L12FqN0t722MLicense: NCBI GEO policy
Part of collection
Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples→ 4 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- skin of body
- Condition
- melanoma
- Modality
- RNA
- Observations (spots)
- 4,991
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,986 × 2,000 px
- mpp
- 3.414 µm/px
- Size
- 54.2 MB
- Sample ID
- GSM7657719
- License
- NCBI GEO policy
- Published
- May 21, 2024
Cite this dataset
doi.org/10.1016/j.crmeth.2024.100759 ↗ BibTeX
@article{Domanskyi_2024,
title = {Nextflow pipeline for Visium and H&E data from patient-derived xenograft samples},
volume = {4},
ISSN = {2667-2375},
url = {http://dx.doi.org/10.1016/j.crmeth.2024.100759},
DOI = {10.1016/j.crmeth.2024.100759},
number = {5},
journal = {Cell Reports Methods},
publisher = {Elsevier BV},
author = {Domanskyi, Sergii and Srivastava, Anuj and Kaster, Jessica and Li, Haiyin and Herlyn, Meenhard and Rubinstein, Jill C. and Chuang, Jeffrey H.},
year = {2024},
month = May,
pages = {100759}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB