Visium

Mouse brain

GSM6886506

bronze Interactive viewer Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'GSM6886506_V11D08-304_B1_hires_image': DataArray[cyx] (3, 1874, 2000)
├── Shapes
│     └── 'GSM6886506_V11D08-304_B1': GeoDataFrame shape: (4332, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4332, 32285)
with coordinate systems:
    ▸ 'GSM6886506_V11D08-304_B1', with elements:
        GSM6886506_V11D08-304_B1_hires_image (Images), GSM6886506_V11D08-304_B1 (Shapes)
    ▸ 'GSM6886506_V11D08-304_B1_downscaled_hires', with elements:
        GSM6886506_V11D08-304_B1_hires_image (Images), GSM6886506_V11D08-304_B1 (Shapes)
    ▸ 'GSM6886506_V11D08-304_B1_downscaled_lowres', with elements:
        GSM6886506_V11D08-304_B1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("jZWW7Nnq0bO4Ef8l0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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("jZWW7Nnq0bO4Ef8l")   # 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download jZWW7Nnq0bO4Ef8l0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/jZWW7Nnq0bO4Ef8l

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid jZWW7Nnq0bO4Ef8l

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples→

14 datasets · time course

Metadata

Technology: Visium
Organism: mouse
Tissue: brain
Modality: RNA
Observations (spots): 4,332
Tier: bronze
Chemistry: Visium v1
Size: 45.6 MB
Sample ID: GSM6886506
License: NCBI GEO policy
Published: Dec 25, 2022

Cite this dataset

doi.org/10.1038/s41467-023-36071-5 ↗

BibTeX

@article{Mirzazadeh_2023,
  title = {Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-36071-5},
  DOI = {10.1038/s41467-023-36071-5},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Mirzazadeh, Reza and Andrusivova, Zaneta and Larsson, Ludvig and Newton, Phillip T. and Galicia, Leire Alonso and Abalo, Xesús M. and Avijgan, Mahtab and Kvastad, Linda and Denadai-Souza, Alexandre and Stakenborg, Nathalie and Firsova, Alexandra B. and Shamikh, Alia and Jurek, Aleksandra and Schultz, Niklas and Nistér, Monica and Samakovlis, Christos and Boeckxstaens, Guy and Lundeberg, Joakim},
  year = {2023},
  month = Jan
}

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB