Visium
Mouse brain
GSM7708221
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'GSM7708221_Control09_hires_image': DataArray[cyx] (3, 2000, 1977)
├── Shapes
│ └── 'GSM7708221_Control09': GeoDataFrame shape: (1266, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1266, 32285)
with coordinate systems:
▸ 'GSM7708221_Control09', with elements:
GSM7708221_Control09_hires_image (Images), GSM7708221_Control09 (Shapes)
▸ 'GSM7708221_Control09_downscaled_hires', with elements:
GSM7708221_Control09_hires_image (Images), GSM7708221_Control09 (Shapes)
▸ 'GSM7708221_Control09_downscaled_lowres', with elements:
GSM7708221_Control09 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("WxX5buc2U5srXTEN0000")
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("WxX5buc2U5srXTEN") # 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 WxX5buc2U5srXTEN0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/WxX5buc2U5srXTEN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid WxX5buc2U5srXTENLicense: NCBI GEO policy
Part of collection
Spatial transcriptomics map of the embryonic mouse brain: a tool to explore neurogenesis→ 4 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations (spots)
- 1,266
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,977 × 2,000 px
- mpp
- 3.322 µm/px
- Size
- 18.4 MB
- Sample ID
- GSM7708221
- License
- NCBI GEO policy
- Published
- Oct 12, 2023
Cite this dataset
doi.org/10.1242/bio.060151 ↗ BibTeX
@article{Di_Marco_2023,
title = {Spatial transcriptomics map of the embryonic mouse brain – a tool to explore neurogenesis},
volume = {12},
ISSN = {2046-6390},
url = {http://dx.doi.org/10.1242/bio.060151},
DOI = {10.1242/bio.060151},
number = {10},
journal = {Biology Open},
publisher = {The Company of Biologists},
author = {Di Marco, Barbara and Vázquez-Marín, Javier and Monyer, Hannah and Centanin, Lázaro and Alfonso, Julieta},
year = {2023},
month = Oct
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB