https://github.com/zhangxiaoyu11/OmiTrans

The first GANs-based omics-to-omics translation framework
https://github.com/zhangxiaoyu11/OmiTrans

cancer-data cancer-genomics deep-learning gans-models generative-adversarial-network omics-data

Last synced: 5 months ago
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The first GANs-based omics-to-omics translation framework

• Host: GitHub
• URL: https://github.com/zhangxiaoyu11/OmiTrans
• Owner: zhangxiaoyu11
• License: mit
• Created: 2021-11-26T04:41:59.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2023-09-05T02:03:27.000Z (about 2 years ago)
• Last Synced: 2024-10-29T18:07:16.093Z (12 months ago)
• Topics: cancer-data, cancer-genomics, deep-learning, gans-models, generative-adversarial-network, omics-data
• Language: Python
• Homepage:
• Size: 9.86 MB
• Stars: 10
• Watchers: 2
• Forks: 5
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# OmiTrans

***Please also have a look at our multi-omics multi-task DL freamwork 👀:***

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

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**The FIRST GANs-based omics-to-omics translation framework**

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

Data Science Institute, Imperial College London

## Introduction

OmiTrans is a generative adversarial networks (GANs) based omics-to-omics translation framework.

## 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+

    -   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/OmiTrans.git

cd OmiTrans

```

-   Install the dependencies

    -   For conda users  

    ```bash

    conda env create -f environment.yml

    conda activate omitrans

    ```

    -   For pip users

    ```bash

    pip install -r requirements.txt

    ```

### Try it out

-   Put the gene expression data (A.tsv) and DNA methylation data (B.tsv) in the default data path (./data)

-   Train and test using 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

```

## OmiEmbed

***Please also have a look at our multi-omics multi-task DL freamwork 👀:***

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

## License

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