Visium
Human intestine
MISC67
silver Interactive viewer H&E colon adenocarcinoma ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ └── 'MISC67_full_image': DataTree[cyx] (3, 30768, 32871), (3, 15384, 16435), (3, 7692, 8217), (3, 3846, 4108)
├── Shapes
│ └── 'MISC67_spots': GeoDataFrame shape: (2551, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2551, 19384)
with coordinate systems:
▸ 'global', with elements:
MISC67_full_image (Images), MISC67_spots (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("gLJ2wJy44Esyq6ik0000")
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("gLJ2wJy44Esyq6ik") # 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 gLJ2wJy44Esyq6ik0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/gLJ2wJy44Esyq6ik
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid gLJ2wJy44Esyq6ikLicense: CC BY-NC-SA 4.0 (noncommercial)
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- intestine
- Condition
- colon adenocarcinoma
- Modality
- RNA
- Observations (spots)
- 2,551
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 40x
- Resolution
- 32,871 × 30,768 px
- mpp
- 0.276 µm/px
- Size
- 2.3 GB
- Sample ID
- MISC67
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Dec 7, 2023
Cite this dataset
doi.org/10.1016/j.cell.2021.11.031 ↗ BibTeX
@article{Chen_2021,
title = {Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps},
volume = {184},
ISSN = {0092-8674},
url = {http://dx.doi.org/10.1016/j.cell.2021.11.031},
DOI = {10.1016/j.cell.2021.11.031},
number = {26},
journal = {Cell},
publisher = {Elsevier BV},
author = {Chen, Bob and Scurrah, Cherie’ R. and McKinley, Eliot T. and Simmons, Alan J. and Ramirez-Solano, Marisol A. and Zhu, Xiangzhu and Markham, Nicholas O. and Heiser, Cody N. and Vega, Paige N. and Rolong, Andrea and Kim, Hyeyon and Sheng, Quanhu and Drewes, Julia L. and Zhou, Yuan and Southard-Smith, Austin N. and Xu, Yanwen and Ro, James and Jones, Angela L. and Revetta, Frank and Berry, Lynne D. and Niitsu, Hiroaki and Islam, Mirazul and Pelka, Karin and Hofree, Matan and Chen, Jonathan H. and Sarkizova, Siranush and Ng, Kimmie and Giannakis, Marios and Boland, Genevieve M. and Aguirre, Andrew J. and Anderson, Ana C. and Rozenblatt-Rosen, Orit and Regev, Aviv and Hacohen, Nir and Kawasaki, Kenta and Sato, Toshiro and Goettel, Jeremy A. and Grady, William M. and Zheng, Wei and Washington, M. Kay and Cai, Qiuyin and Sears, Cynthia L. and Goldenring, James R. and Franklin, Jeffrey L. and Su, Timothy and Huh, Won Jae and Vandekar, Simon and Roland, Joseph T. and Liu, Qi and Coffey, Robert J. and Shrubsole, Martha J. and Lau, Ken S.},
year = {2021},
month = Dec,
pages = {6262–6280.e26}
}Source: cell.com ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB