Visium
Human locus ceruleus
GSM9233011
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9233011_V13M06-333_B1_hires_image': DataArray[cyx] (3, 2000, 1892)
│ └── 'GSM9233011_V13M06-333_B1_lowres_image': DataArray[cyx] (3, 600, 568)
├── Shapes
│ └── 'GSM9233011_V13M06-333_B1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 36601)
with coordinate systems:
▸ 'GSM9233011_V13M06-333_B1', with elements:
GSM9233011_V13M06-333_B1_hires_image (Images), GSM9233011_V13M06-333_B1_lowres_image (Images), GSM9233011_V13M06-333_B1 (Shapes)
▸ 'GSM9233011_V13M06-333_B1_downscaled_hires', with elements:
GSM9233011_V13M06-333_B1_hires_image (Images), GSM9233011_V13M06-333_B1 (Shapes)
▸ 'GSM9233011_V13M06-333_B1_downscaled_lowres', with elements:
GSM9233011_V13M06-333_B1_lowres_image (Images), GSM9233011_V13M06-333_B1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("I4aqdQmO9QBC61Hh0000")
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("I4aqdQmO9QBC61Hh") # 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 I4aqdQmO9QBC61Hh0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/I4aqdQmO9QBC61Hh
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid I4aqdQmO9QBC61HhLicense: NCBI GEO policy
Part of collection
Impact of Alzheimer’s disease risk factors and local neuromelanin content on the transcriptomic landscape of the human locus coeruleus→ 43 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- locus ceruleus
- Modality
- RNA
- Observations (spots)
- 4,992
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,892 × 2,000 px
- mpp
- 4.074 µm/px
- Size
- 30.1 MB
- Sample ID
- GSM9233011
- License
- NCBI GEO policy
- Published
- Feb 16, 2026
Cite this dataset
doi.org/10.1101/2025.10.29.685354 ↗ BibTeX
@article{Mulvey_2025,
title = {Impact of Alzheimer’s disease risk factors and local neuromelanin content on the transcriptomic landscape of the human locus coeruleus},
url = {http://dx.doi.org/10.1101/2025.10.29.685354},
DOI = {10.1101/2025.10.29.685354},
publisher = {openRxiv},
author = {Mulvey, Bernard and Divecha, Heena R. and Tippani, Madhavi and Bach, Svitlana V. and Bharadwaj, Rahul and Del Rosario, Ishbel and Maguire, Sarah E. and Miller, Ryan A. and Salisbury, Aaron J. and Chandra, Atharv and Oster, Beau A. and Montgomery, Kelsey D. and Kwon, Sang Ho and Algrain, Haya A. and Papariello, Alexis R. and Huuki-Myers, Louise A. and Kleinman, Joel E. and Collado-Torres, Leonardo and Hyde, Thomas M. and Han, Shizhong and Hicks, Stephanie C. and Weinberger, Daniel R. and Page, Stephanie C. and Maynard, Kristen R. and Martinowich, Keri},
year = {2025},
month = Oct
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB