spatialMETA: a deep learning framework for spatial multiomics
Project description
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file spatialMETA-0.0.2.3-py3-none-any.whl.
File metadata
- Download URL: spatialMETA-0.0.2.3-py3-none-any.whl
- Upload date:
- Size: 131.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.21
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
85b33796e96bdc177f79614eb09ef52af04488c1b761800385e439e9d63cb15a
|
|
| MD5 |
5179552b8f512076be065c0f21d74e5f
|
|
| BLAKE2b-256 |
b56815d35c11ca4fd88e4d40bc6383854dff67814629d39c1f56a0fe82f26aac
|
