SpatialMETA
spatialMETA is a method for integrating spatial multi-omics data. SMOI aligns ST and SM to a unified resolution, integrates single or multiple sample data to identify cross-modal spatial patterns, and offers extensive visualization and analysis functions.
Documentation
Installation
Recommended to use Python 3.9 environment.
Installing via PyPI
pip3 install spatialmeta
Installing from source
git clone git@github.com:WanluLiuLab/SpatialMETA.git
cd spatialmeta
pip3 install -r requirements.txt
python3 setup.py install
Create a new environment
# This will create a new environment named spatialmeta
conda env create -f environment.yml
conda activate spatialmeta
Change Log
- 0.0.2 (2025-03-06)
- Update
spatialmeta.model.AlignmentModule - Update
spatialmeta.model.ConditionalVAESTSM
- Update
1 maintainer
Metadata
1 maintainer
Release files for spatialMETA 0.0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| spatialMETA-0.0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Release files / spatialMETA-0.0.3.0-py3-none-any.whl
| Download URL | spatialMETA-0.0.3.0-py3-none-any.whl |
|---|---|
| Size | 12.7 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a2327e9ff845a7a88acc7d9929f6a41a3cdb49c0a84b89f63705b5c099ef001c
|
|
BLAKE2b-256 checksum How to use checksums |
f06520d956dcb25523041c403a7089ff376b8804f398ddfa5af1233123e5a123
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.9.21
|
