MOGDx v1.0 Release

This release has been developed for the ISMB conference paper submission. Multi-omic Graph Diagnosis (MOGDx) is a tool for the integration of omic data and classification of heterogeneous diseases

Key Features

1. Genomic Data Integration

• Integrate any number of modalities
• Flexibility in choice of omics integrated

2. Network Taxonomy

• Represents omic information using a patient similarity metric
• Uses Similarity Network Fusion to integrate multiple omics

3. Graph Convolutional Network with Multi Modal Encoder

• Reduces multiple modalities in a supervised manner using multi modal encoder
• Performs patient classification using graph convolutional network framework

How to Use

See README.md for instructions of use

Citation

If you use MOGDx in your research, please cite our ISMB conference paper once it is published or our preprint on medRxiv

Feedback and Contributions

We welcome your feedback and contributions! Feel free to open an issue on our GitHub for bug reports, feature requests, or general inquiries.

Thank you for choosing MOGDx for your multi omic integration, nees We look forward to your contributions and the advancement of genomics research.