Visium
Mouse thymus
GSM7097916
silver Interactive viewer H&E asthma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7097916_tdKO_bio1_tech2_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│ ├── 'GSM7097916_tdKO_bio1_tech2_hires_image': DataArray[cyx] (3, 2000, 1804)
│ └── 'GSM7097916_tdKO_bio1_tech2_lowres_image': DataArray[cyx] (3, 600, 541)
├── Shapes
│ └── 'GSM7097916_tdKO_bio1_tech2': GeoDataFrame shape: (2452, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2452, 19465)
with coordinate systems:
▸ 'GSM7097916_tdKO_bio1_tech2', with elements:
GSM7097916_tdKO_bio1_tech2_full_image (Images), GSM7097916_tdKO_bio1_tech2_hires_image (Images), GSM7097916_tdKO_bio1_tech2_lowres_image (Images), GSM7097916_tdKO_bio1_tech2 (Shapes)
▸ 'GSM7097916_tdKO_bio1_tech2_downscaled_hires', with elements:
GSM7097916_tdKO_bio1_tech2_hires_image (Images), GSM7097916_tdKO_bio1_tech2 (Shapes)
▸ 'GSM7097916_tdKO_bio1_tech2_downscaled_lowres', with elements:
GSM7097916_tdKO_bio1_tech2_lowres_image (Images), GSM7097916_tdKO_bio1_tech2 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("UCKelD9LxzRnkWND") # 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/UCKelD9LxzRnkWND
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid UCKelD9LxzRnkWND Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["UCKelD9LxzRnkWND0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
The transcription factor Zfp281 serves redundantly with Zfp148 to support CD4+ T cell development and functions [Thymus Visium]→ 6 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- thymus
- Condition
- asthma
- Modality
- RNA
- Observations
- 2,452
- Tier
- silver
- Chemistry
- Visium CytAssist v2
- Resolution
- 1,804 × 2,000 px
- mpp
- 3.903 µm/px
- Size
- 52 MB
- Sample ID
- GSM7097916
- License
- NCBI GEO policy
- Published
- Nov 13, 2023
Cite this dataset
doi.org/10.1126/sciimmunol.adi9066 ↗ BibTeX
@article{Chopp_2023,
title = {Zfp281 and Zfp148 control CD4
<sup>+</sup>
T cell thymic development and T
<sub>H</sub>
2 functions},
volume = {8},
ISSN = {2470-9468},
url = {http://dx.doi.org/10.1126/sciimmunol.adi9066},
DOI = {10.1126/sciimmunol.adi9066},
number = {89},
journal = {Science Immunology},
publisher = {American Association for the Advancement of Science (AAAS)},
author = {Chopp, Laura B. and Zhu, Xiaoliang and Gao, Yayi and Nie, Jia and Singh, Jatinder and Kumar, Parimal and Young, Kelly Z. and Patel, Shil and Li, Caiyi and Balmaceno-Criss, Mariah and Vacchio, Melanie S. and Wang, Michael M. and Livak, Ferenc and Merchant, Juanita L. and Wang, Lie and Kelly, Michael C. and Zhu, Jinfang and Bosselut, Rémy},
year = {2023},
month = Nov
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB