The code is used for the work of “Deciphering genetic architecture of brain age gap”. This code includes two parts, the first part is the SACN model, and the second part is the analysis process for the BAG GWAS.
The code for the SACN model, training process, and evaluation process.
- SACN.py, Resnet.py. the network architecture of SACN and resnet
- Evalation.py, the evaluation process for SACN
- fune_tune.py, transfer the pre-trained network to the UKB biobank
- train_c.py, the train and test process
- main.py, the main process for paramater modify
- disorder_classification.py, adopted the stratified feature to classify the AD
- requirements.txt the environment required to run this model
You can run the following command to start the training process
python main.py --root_dir /public/home/zhaoxz/reCOns/full_age1.csv --network_type SACN --model_name SACN --base SACN --epochs 200 --batch_size 12 --lr 1e-04
# network_type one of [base,Gender_AD,Domain_AD,SACN]- PRS.R. the PGS analysis of different phenotypes, and association with BAG
- MR_plot.R, the plot for the MR result
- Expression_analysis.R, the expression analysis of BAG-related gene
- AD_methylation.R, the process of methylation data on ADNI
- TRN_bag.R, the associated analysis of BAG-related gene and MAG-related gene in brain TRN.
- TRN_aging.R, the association between BAG and aging-related pathway
- Disorder_common.R, the pleiotropy of BAG-related gene in diverse brain disorders
- PPI.R, the PPI analysis of BAG-related gene
- cell_type.R, the code for cell type analysis
if you have any questions about this code, please contact the author (18210850006@fudan.edu.cn)