# OmiEmbed

***Please also have a look at our brand new omics-to-omics DL freamwork 👀:***

[OmiTrans](https://github.com/zhangxiaoyu11/OmiTrans)

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**OmiEmbed: A Unified Multi-task Deep Learning Framework for Multi-omics Data**

**Xiaoyu Zhang** (x.zhang18@imperial.ac.uk)

Data Science Institute, Imperial College London

## Introduction

OmiEmbed is a unified framework for deep learning-based omics data analysis, which supports:

1.  Multi-omics integration

2.  Dimensionality reduction

3.  Omics embedding learning

4.  Tumour type classification

5.  Phenotypic feature reconstruction

6.  Survival prediction

7.  Multi-task learning for aforementioned tasks

Paper Link: [https://doi.org/10.3390/cancers13123047](https://doi.org/10.3390/cancers13123047)

## Getting Started

### Prerequisites

-   CPU or NVIDIA GPU + CUDA CuDNN

-   [Python](https://www.python.org/downloads) 3.6+

-   Python Package Manager

    -   [Anaconda](https://docs.anaconda.com/anaconda/install) 3 (recommended)

    -   or [pip](https://pip.pypa.io/en/stable/installing/) 21.0+

-   Python Packages

    -   [PyTorch](https://pytorch.org/get-started/locally) 1.2+

    -   TensorBoard 1.10+

    -   Tables 3.6+

    -   scikit-survival 0.6+

    -   prefetch-generator 1.0+

-   [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) 2.7+

### Installation

-   Clone the repo

```bash

git clone https://github.com/zhangxiaoyu11/OmiEmbed.git

cd OmiEmbed

```

-   Install the dependencies

    -   For conda users  

    ```bash

    conda env create -f environment.yml

    conda activate omiembed

    ```

    -   For pip users

    ```bash

    pip install -r requirements.txt

    ```

### Try it out

-   Train and test using the built-in sample dataset with the default settings

```bash

python train_test.py

```

-   Check the output files

```bash

cd checkpoints/test/

```

-   Visualise the metrics and losses

```bash

tensorboard --logdir=tb_log --bind_all

```

## Citation

If you use this code in your research, please cite our paper.

```bibtex

@Article{OmiEmbed2021,

    AUTHOR = {Zhang, Xiaoyu and Xing, Yuting and Sun, Kai and Guo, Yike},

    TITLE = {OmiEmbed: A Unified Multi-Task Deep Learning Framework for Multi-Omics Data},

    JOURNAL = {Cancers},

    VOLUME = {13},

    YEAR = {2021},

    NUMBER = {12},

    ARTICLE-NUMBER = {3047},

    ISSN = {2072-6694},

    DOI = {10.3390/cancers13123047}

}

```

## OmiTrans

***Please also have a look at our brand new omics-to-omics DL freamwork 👀:***

[OmiTrans](https://github.com/zhangxiaoyu11/OmiTrans)

## License

This source code is licensed under the [MIT](https://github.com/zhangxiaoyu11/OmiEmbed/blob/main/LICENSE) license.