10x Xenium
Mouse hair follicle
GSM8546224
bronze Interactive viewer injury Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataArray[cyx] (1, 30589, 34173)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (30589, 34173), (15294, 17086), (7647, 8543), (3823, 4271), (1911, 2135)
│ └── 'nucleus_labels': DataTree[yx] (30589, 34173), (15294, 17086), (7647, 8543), (3823, 4271), (1911, 2135)
├── Points
│ └── 'transcripts': DataFrame with shape: (8275955, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (32760, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (32760, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (32760, 2) (2D shapes)
└── Tables
└── 'table': AnnData (32760, 479)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("j6aTWbgoV2W3PdfV0000")
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("j6aTWbgoV2W3PdfV") # 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 j6aTWbgoV2W3PdfV0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/j6aTWbgoV2W3PdfV
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid j6aTWbgoV2W3PdfVLicense: NCBI GEO policy
Part of collection
In situ targeted gene expression analysis of healing skin on SD0 post-wounding in Wildtype and Rnasel knock out wounds→ 6 datasets · comparison
Metadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- hair follicle
- Condition
- injury
- Modality
- RNA
- Observations (cells)
- 32,760
- Transcripts
- 8,275,955
- Tier
- bronze
- Size
- 723 MB
- Sample ID
- GSM8546224
- License
- NCBI GEO policy
- Published
- Feb 8, 2025
Cite this dataset
doi.org/10.1172/jci172595 ↗ BibTeX
@article{Kirby_2025,
title = {RNase L represses hair follicle regeneration through altered innate immune signaling},
volume = {135},
ISSN = {1558-8238},
url = {http://dx.doi.org/10.1172/jci172595},
DOI = {10.1172/jci172595},
number = {6},
journal = {Journal of Clinical Investigation},
publisher = {American Society for Clinical Investigation},
author = {Kirby, Charles S. and Islam, Nasif and Wier, Eric and Alphonse, Martin P. and Sweren, Evan and Wang, Gaofeng and Liu, Haiyun and Kim, Dongwon and Li, Ang and Lee, Sam S. and Overmiller, Andrew M. and Xue, Yingchao and Reddy, Sashank and Archer, Nathan K. and Miller, Lloyd S. and Yu, Jianshi and Huang, Weiliang and Jones, Jace W. and Kim, Sooah and Kane, Maureen A. and Silverman, Robert H. and Garza, Luis A.},
year = {2025},
month = Feb
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB