Metadata-Version: 2.1
Name: PathIntegrate
Version: 0.0.4
Summary: PathIntegrate: multivariate modelling approaches for pathway-based muti-omics integration
Home-page: https://github.com/cwieder/PathIntegrate
Author: Cecilia Wieder
Author-email: cw2019@ic.ac.uk
License: GNU 3.0
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cmcrameri
Requires-Dist: dash
Requires-Dist: dash_bootstrap_components
Requires-Dist: dash_cytoscape
Requires-Dist: datauri
Requires-Dist: mbpls
Requires-Dist: networkx
Requires-Dist: setuptools
Requires-Dist: sspa>=1.0.1
Requires-Dist: statsmodels
Requires-Dist: svgwrite

# PathIntegrate
PathIntegrate Python package for pathway-based multi-omics data integration

![PathIntegrate graphical abstract](ModellingFrameworks_white.png "PathIntegrate graphical abstract")

#### Abstract
>As terabytes of multi-omics data are being generated, there is an ever-increasing need for methods facilitating the integration and interpretation of such data. Current multi-omics integration methods typically output lists, clusters, or subnetworks of molecules related to an outcome. Even with expert domain knowledge, discerning the biological processes involved is a time-consuming activity. Here we propose PathIntegrate, a method for integrating multi-omics datasets based on pathways, designed to exploit knowledge of biological systems and thus provide interpretable models for such studies. PathIntegrate employs single-sample pathway analysis to transform multi-omics datasets from the molecular to the pathway-level, and applies a predictive single-view or multi-view model to integrate the data. Model outputs include multi-omics pathways ranked by their contribution to the outcome prediction, the contribution of each omics layer, and the importance of each molecule in a pathway. 

## Features
- Pathway-based multi-omics data integration using PathIntegrate Multi-View and Single-View models
    - Multi-View model: Integrates multiple omics datasets using a shared pathway-based latent space
    - Single-View model: Integrates multi-omics data into one set of multi-omics pathway scores and applies an SKlearn-compatible predictive model
    - Pathway importance
    - Sample prediction
- SKlearn-like API for easy integration into existing pipelines
- Support for multiple pathway databases, including KEGG, Reactome, PathBank, and custom GMT files 
- Support for multiple pathway scoring methods available via the [sspa](https://github.com/cwieder/py-ssPA) package
- Cytoscape Network Viewer app for visualizing pathway-based multi-omics data integration results

![PathIntegrate Cytoscape app](App_network_view.JPG "Network viewer")

## System requirements
### Hardware
At least 8BG RAM recommended. PathIntegrate models can run on a Google Colab notebook server (see walkthrough tutorial below with example data).

### Software
PathIntegrate has been tested on MacOs, Windows 10 and Linux. Python 3.10 or higher is required. Python dependencies are listed in the requirements.txt file.

## Installation
```bash
pip install PathIntegrate
```

## Tutorials and documentation
Please see our Quickstart guide on [Google Colab](https://colab.research.google.com/drive/1nv9lp8mMQ2Yk8n9uI9hBMvH71MlWp3UJ?usp=sharing)

Full documentation and function reference for PathIntegrate can be found via our [ReadTheDocs page](https://cwieder.github.io/PathIntegrate/)

## Citing PathIntegrate
If you use PathIntegrate in your research, please consider citing our paper:
```bibtex
@article{Wieder2024,
   author = {Cecilia Wieder and Juliette Cooke and Clement Frainay and Nathalie Poupin and Russell Bowler and Fabien Jourdan and Katerina J. Kechris and Rachel P.J. Lai and Timothy Ebbels},
   doi = {10.1371/JOURNAL.PCBI.1011814},
   issue = {3},
   journal = {PLOS Computational Biology},
   month = {3},
   pages = {e1011814},
   pmid = {38527092},
   publisher = {Public Library of Science},
   title = {PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration},
   volume = {20},
   url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011814},
   year = {2024},
}
```

## License
GNU GPL v3
