spatial CUT&Tag

Mouse brain

GSM6753044

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Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'tissue_hires': DataArray[cyx] (3, 3181, 3181)
├── Shapes
│     ├── 'epi_spots': GeoDataFrame shape: (9752, 1) (2D shapes)
│     └── 'epi_spots_for_vitessce': GeoDataFrame shape: (9752, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (9752, 25881)
with coordinate systems:
    ▸ 'global', with elements:
        tissue_hires (Images), epi_spots (Shapes), epi_spots_for_vitessce (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("bQuu5QyOsIpx0YEG0000")
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("bQuu5QyOsIpx0YEG")   # 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 bQuu5QyOsIpx0YEG0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/bQuu5QyOsIpx0YEG

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid bQuu5QyOsIpx0YEG

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Spatial epigenome-transcriptome co-profiling of mammalian tissues→

6 datasets · time course

Metadata

Technology: spatial CUT&Tag
Organism: mouse
Tissue: brain
Modality: Epigenomics
Observations: 9,752
Tier: bronze
Resolution: 3,181 × 3,181 px
mpp: 20.000 µm/px
Size: 85.1 MB
Sample ID: GSM6753044
License: NCBI GEO policy
Published: Jan 29, 2023

Cite this dataset

doi.org/10.1038/s41586-023-05795-1 ↗

BibTeX

@article{Zhang_2023,
  title = {Spatial epigenome–transcriptome co-profiling of mammalian tissues},
  volume = {616},
  ISSN = {1476-4687},
  url = {http://dx.doi.org/10.1038/s41586-023-05795-1},
  DOI = {10.1038/s41586-023-05795-1},
  number = {7955},
  journal = {Nature},
  publisher = {Springer Science and Business Media LLC},
  author = {Zhang, Di and Deng, Yanxiang and Kukanja, Petra and Agirre, Eneritz and Bartosovic, Marek and Dong, Mingze and Ma, Cong and Ma, Sai and Su, Graham and Bao, Shuozhen and Liu, Yang and Xiao, Yang and Rosoklija, Gorazd B. and Dwork, Andrew J. and Mann, J. John and Leong, Kam W. and Boldrini, Maura and Wang, Liya and Haeussler, Maximilian and Raphael, Benjamin J. and Kluger, Yuval and Castelo-Branco, Gonçalo and Fan, Rong},
  year = {2023},
  month = Mar,
  pages = {113–122}
}

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