deepGBLUP: Integration of deep learning and GBLUP for accurate genomic prediction.

Model summary

This repo is the official Code of deepGBLUP: joint deep learning networks and GBLUP framework for accurate genomic prediction of complex traits in Korean native cattle. For model details, please refer to the paper [link].

Implementation

0. Requirements

We build deepGBLUP on the Python 3.9, Ubuntu 18.04, and cuda11.3. We recommend anaconda environment for deepGBLUP.

1. Installation

1. Clone this repository
2. Build the virtual environment

conda create -n venv python=3.9
conda activate venv

3. Install pytorch:

# For CUDA 11.3
conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge

# For CPU Only
conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cpuonly -c pytorch

3. Install requirements

pip install -r requirements.txt

2. Excution

0. Input Data format

1) raw

The genotype data of plink. See https://www.cog-genomics.org/plink2/formats#raw for more details.

2) phenotype

The phenotype data. It is a .txt file involving two columns. First column is animal name, which must match with the one in raw file. Second column is phenotype. deepGBLUP automatically sets the individuals included in raw file but not in the phenotype file as test individuals. See data/1000_samples.phen as an example format.

1. Open the 'main.py' file with text editor and set configuration. You can implement deepGBLUP with sample data by using default configuration.

# data path
raw_path: path of raw file
phen_path: path of phenotype file
bim_path (optional): path of bim file to save SNP effects. If you don't have bim file just type None 

# train cofig
lr: learning rate
epoch: epoch
batch_size: batch_size
device: type 'cpu' if you use cpu device, or type 'cuda' if you use gpu device.
h2: heritability

# save config
save_path: path to save results

2. Run deepGBLUP

python main.py

3. Output files

last.pth: trained weights file
log.txt: training log file
setting.txt: text file to save configuration
sol.txt: text file to save individuals' gEBV.