--- a +++ b/README.md @@ -0,0 +1,42 @@ +# OmiVAE +***Please check the updated version of OmiVAE:*** +[OmiEmbed](https://github.com/zhangxiaoyu11/OmiEmbed) + +[](https://zenodo.org/badge/latestdoi/201760678) +[](https://github.com/zhangxiaoyu11/OmiVAE/blob/master/LICENSE) + +[](https://github.com/zhangxiaoyu11/OmiVAE/stargazers) +[](https://github.com/zhangxiaoyu11/OmiVAE/network/members) + +**OmiVAE: Integrated Multi-omics Analysis Using Variational Autoencoders** + +**Xiaoyu Zhang** (x.zhang18@imperial.ac.uk) + +Data Science Institute, Imperial College London + +## Introduction + +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](https://arxiv.org/abs/1908.06278) + +## Citation +If you use this code for your research, please cite our paper. +```bibtex +@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} +} +``` + +## OmiEmbed +***Please check the updated version of OmiVAE***: +[OmiEmbed](https://github.com/zhangxiaoyu11/OmiEmbed) + +## License +This source code is licensed under the [MIT](https://github.com/zhangxiaoyu11/OmiVAE/blob/master/LICENSE) license. +