Convolutional neural network to predict immune cell chromatin state
May 29, 2023 ยท View on GitHub
Convolutional neural network to predict immune cell chromatin state
AI-TAC is a deep convoluional network for predicting mouse immune cell ATAC-seq signal from peak sequences using data from the Immunological Genome Project: http://www.immgen.org/.
Requirements
The code was written in python v3.6.3 and pytorch v1.4.0, and run on NVIDIA P100 Pascal GPUs.
Tutorial
The processed data files can be downloaded using the following links:
The required input is a bed file with ATAC-seq peak locations, the reference genome and a file with normalized peak heights. The code for processing raw data is in data_processing/; for example, to convert the ImmGen mouse data set to one-hot encoded sequences and save in the data directory, run:
python process_data.py "../data/ImmGenATAC1219.peak_matched.txt" "../data/mouse_peak_heights.csv" "../mm10/" "../data/"
The model can then be trained by running:
python train_test_aitac.py model_name '../data/one_hot_seqs.npy' '../data/cell_type_array.npy' '../data/peak_names.npy'
To extract first layer motifs run:
python -u extract_motifs.py model_name '../data/one_hot_seqs.npy' '../data/cell_type_array.npy' '../data/peak_names.npy'