Visium

Mouse brain

NCBI720

silver Interactive viewer H&E Provisional

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     └── 'NCBI720_full_image': DataTree[cyx] (3, 8192, 7884), (3, 4096, 3942), (3, 2048, 1971), (3, 1024, 985)
├── Shapes
│     └── 'NCBI720_spots': GeoDataFrame shape: (2573, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2573, 32285)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI720_full_image (Images), NCBI720_spots (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("QXfgUUTDRWUrNPgR")   # 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

Load from the CLI

# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/QXfgUUTDRWUrNPgR

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid QXfgUUTDRWUrNPgR

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["QXfgUUTDRWUrNPgR0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

Spatial transcriptomics of the mouse brain across three age groups→

6 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: brain
Modality: RNA
Observations: 2,573
Tier: silver
Chemistry: Visium v1
Resolution: 7,884 × 8,192 px
mpp: 1.111 µm/px
Size: 206 MB
Sample ID: NCBI720
License: CC BY-NC-SA 4.0 NonCommercial
Published: Apr 17, 2023

Cite this dataset

doi.org/10.1016/j.cell.2023.07.027 ↗

BibTeX

@article{Hahn_2023,
  title = {Atlas of the aging mouse brain reveals white matter as vulnerable foci},
  volume = {186},
  ISSN = {0092-8674},
  url = {http://dx.doi.org/10.1016/j.cell.2023.07.027},
  DOI = {10.1016/j.cell.2023.07.027},
  number = {19},
  journal = {Cell},
  publisher = {Elsevier BV},
  author = {Hahn, Oliver and Foltz, Aulden G. and Atkins, Micaiah and Kedir, Blen and Moran-Losada, Patricia and Guldner, Ian H. and Munson, Christy and Kern, Fabian and Pálovics, Róbert and Lu, Nannan and Zhang, Hui and Kaur, Achint and Hull, Jacob and Huguenard, John R. and Grönke, Sebastian and Lehallier, Benoit and Partridge, Linda and Keller, Andreas and Wyss-Coray, Tony},
  year = {2023},
  month = Sept,
  pages = {4117–4133.e22}
}

Source: NCBI GEO ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB