Visium
Human lung
GSM8217624
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8217624_GW_15_hires_image': DataArray[cyx] (3, 2000, 1767)
│ └── 'GSM8217624_GW_15_lowres_image': DataArray[cyx] (3, 600, 530)
├── Shapes
│ └── 'GSM8217624_GW_15': GeoDataFrame shape: (3949, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3949, 18085)
with coordinate systems:
▸ 'GSM8217624_GW_15', with elements:
GSM8217624_GW_15_hires_image (Images), GSM8217624_GW_15_lowres_image (Images), GSM8217624_GW_15 (Shapes)
▸ 'GSM8217624_GW_15_downscaled_hires', with elements:
GSM8217624_GW_15_hires_image (Images), GSM8217624_GW_15 (Shapes)
▸ 'GSM8217624_GW_15_downscaled_lowres', with elements:
GSM8217624_GW_15_lowres_image (Images), GSM8217624_GW_15 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("wTfsUDConqvgygSj0000")
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("wTfsUDConqvgygSj") # 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 wTfsUDConqvgygSj0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/wTfsUDConqvgygSj
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid wTfsUDConqvgygSjLicense: NCBI GEO policy
Part of collection
Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity [Visium]→ 2 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- lung
- Modality
- RNA
- Observations (spots)
- 3,949
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,767 × 2,000 px
- mpp
- 4.499 µm/px
- Size
- 95.6 MB
- Sample ID
- GSM8217624
- License
- NCBI GEO policy
- Published
- Jun 4, 2024
Cite this dataset
doi.org/10.1038/s41467-024-50281-5 ↗ BibTeX
@article{Quach_2024,
title = {Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity},
volume = {15},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-024-50281-5},
DOI = {10.1038/s41467-024-50281-5},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Quach, Henry and Farrell, Spencer and Wu, Ming Jia Michael and Kanagarajah, Kayshani and Leung, Joseph Wai-Hin and Xu, Xiaoqiao and Kallurkar, Prajkta and Turinsky, Andrei L. and Bear, Christine E. and Ratjen, Felix and Kalish, Brian and Goyal, Sidhartha and Moraes, Theo J. and Wong, Amy P.},
year = {2024},
month = July
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB