SPatial transcriptomics Analysis via Cell Embedding
Project description
Spatial transcriptomics data analysis via interaction-aware cell embedding reveals cell communities with characteristic cell-cell interactions
SPACE (SPatial transcriptomics Analysis via Cell Embedding)
Installation
install from PyPI
pip install space-srt
install from GitHub
install the latest develop version
git clone https://github.com/zhangqf-lab/SPACE.git
cd SPACE
python setup.py install
SPACE is implemented in Pytorch framework.
SPACE can be run on CPU devices, and running SPACE on GPU devices if available is recommended.
Tutorial
A brief tutorial can be found here.(Still in progress)
Citation
If you use SPACE in your research, please cite our paper:
Li, Y., Zhang J., Gao, X., and Zhang, Q.C. Tissue module discovery in single-cell resolution spatial transcriptomics data via cell- cell interaction-aware cell embedding. Cell Systems 2024 (Accepted)
Project details
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 Distribution
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 space_srt-0.7.0.tar.gz.
File metadata
- Download URL: space_srt-0.7.0.tar.gz
- Upload date:
- Size: 11.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.10.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9c4f938b950cc2ed6bc496874e16a5891d1e5a80f177b6994b7e0b1d8945af10
|
|
| MD5 |
c893fe9d9e602e8ac0a766dd9f6a87f3
|
|
| BLAKE2b-256 |
4cf6d5c05b2f0d40ac9b086386fd65ac75de298b967507bbfb01e05e2652e688
|
File details
Details for the file space_srt-0.7.0-py3-none-any.whl.
File metadata
- Download URL: space_srt-0.7.0-py3-none-any.whl
- Upload date:
- Size: 12.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.10.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
80827a58930e46735db15829840df9545334802dd46cd9912fba037afd692600
|
|
| MD5 |
8177de1cd97a4858c42120c501f7651a
|
|
| BLAKE2b-256 |
0ce599966a4b497e8db0c1a31ac226dda251aa47fb387ec9b5082f58827a14e7
|