spatial ATAC-seq
Mouse brain
GSM6753043
bronze Interactive viewer H&E ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'tissue_hires': DataArray[cyx] (3, 2334, 2332)
├── Shapes
│ ├── 'epi_spots': GeoDataFrame shape: (9215, 1) (2D shapes)
│ └── 'epi_spots_for_vitessce': GeoDataFrame shape: (9215, 2) (2D shapes)
└── Tables
└── 'table': AnnData (9215, 22914)
with coordinate systems:
▸ 'global', with elements:
tissue_hires (Images), epi_spots (Shapes), epi_spots_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("Ek76xy8Hf6OXA1vP0000")
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("Ek76xy8Hf6OXA1vP") # 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 Ek76xy8Hf6OXA1vP0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/Ek76xy8Hf6OXA1vP
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Ek76xy8Hf6OXA1vPLicense: NCBI GEO policy
Part of collection
Spatial epigenome-transcriptome co-profiling of mammalian tissues→ 6 datasets · time course
Metadata
- Technology
- spatial ATAC-seq
- Organism
- mouse
- Tissue
- brain
- Modality
- Epigenomics
- Observations
- 9,215
- Tier
- bronze
- Resolution
- 2,332 × 2,334 px
- mpp
- 20.000 µm/px
- Size
- 44.3 MB
- Sample ID
- GSM6753043
- 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