Please check the updated version of OmiVAE: OmiEmbed
OmiVAE: Integrated Multi-omics Analysis Using Variational Autoencoders
Xiaoyu Zhang ([email protected])
Data Science Institute, Imperial College London
OmiVAE is an end-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.
Accepted by 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019)
Paper Link: arXiv
If you use this code for your research, please cite our paper.
@inproceedings{OmiVAE2019,
title={Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification},
author={Zhang, Xiaoyu and Zhang, Jingqing and Sun, Kai and Yang, Xian and Dai, Chengliang and Guo, Yike},
booktitle={Bioinformatics and Biomedicine (BIBM), 2019 IEEE International Conference on},
year={2019}
}Please check the updated version of OmiVAE: OmiEmbed
This source code is licensed under the MIT license.