A fast and interpretable dimension reduction algorithm for spatial transcriptomics data.
Project description
GraphPCA
GraphPCA is a novel graph-constrained, interpretable, and quasi-linear dimension-reduction method tailored for spatial transcriptomic data. It leverages the strengths of graphical regularization and Principal Component Analysis (PCA) to extract low-dimensional embeddings of spatial transcriptomes that integrate location information in linear time complexity. The substantial power boost enabled by GraphPCA fertilizes various downstream tasks of spatial transcriptomics data analyses and provides more precise insights into transcriptomic and cellular landscapes of complex tissues.
Software dependencies
numpy pandas matplotlib scipy scikit-learn networkx scanpy squidpy
installation
Install GraphPCA via PyPI by using:
pip install st-graphpca
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 st-graphpca-0.1.1.tar.gz.
File metadata
- Download URL: st-graphpca-0.1.1.tar.gz
- Upload date:
- Size: 5.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d5d4d15ba9e670726b0355bed9f6a385f2e88176d672c0bf6c47072c6ac73b9c
|
|
| MD5 |
dd4774cc904fb6de27e78d5ff332ef2d
|
|
| BLAKE2b-256 |
0f3c14c1339a7e5c0ba84b34dee759da37ff854d62e33bd6d8a672f2325ad59e
|
File details
Details for the file st_graphpca-0.1.1-py3-none-any.whl.
File metadata
- Download URL: st_graphpca-0.1.1-py3-none-any.whl
- Upload date:
- Size: 5.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3d97d09dae2f36a7fba73efdc67a84f843a327168d7a0ef42a3726bc831bdba0
|
|
| MD5 |
0cb020180e6ebece786b5a5eb56eeab5
|
|
| BLAKE2b-256 |
1165d5c448c4eab970abff3378ae009f3a9c7f0ad3dcca3cd683d6f60a530fc2
|
