wiedersehne/cdildna

Self-supervised Learning for DNA sequences with circular dilated convolutional networks

paper: https://doi.org/10.1016/j.neunet.2023.12.002.

Overview of cdilDNA with self-supervised learning.

Variant Effect Prediction in Human Tissues.

To pretrain a model you need to follow the steps:

1. Download GRCH38 from http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz. (3.1G)
2. Run generate_pretrain_human.py in ./data/. Sequence length [1k, 5k, 10k] and numbers(100k) are required.
3. Run pretraining.py with the generated data. Configurations of different lengths shall be changed accordingly in config.yaml.

To fine-tune a pretrained model, you need to:

1. Run generate_data.py in ./data/ to save data. The sequence length is required. A total of 97,922 sequence will be extracted. ve_df.csv needs to be loaded.
2. Run classify_lightning.py to load the pretrained model under the folder ./human/100k_pretrain_best_epoch_9_8_16.pt and train cdilDNA.

Experimental Results

Model	Parameters(k)	Running time (ms)	Memory (MB)	AUROC(%)
CDIL w/ pretrain	39.8	14.51	65.22	88.08
CDIL w/o pretrain	39.8	14.52	65.22	87.50
CNN	39.8	11.60	49.03	85.42
Transformer	33.3	66.65	190.05	66.49
Nyströmformer w/ pretrain	42	35.08	133.19	87.71
Nyströmformer w/o pretrain	42	35.08	133.19	87.50
Performer	41.3	24.25	76.44	87.32
Enformer	/	/	/	84.53

varant_effect result

OCR Prediciton in Plants.

To pretrain a model you need to follow the steps:

1. Download reference genome files from https://plantdeepsea-toturial2.readthedocs.io/en/latest/08-Statistics.html to ./data/plants/plant_genome/.
2. Run plant_download.ipynb in ./data/plants/plant_data/ to download plant data.
3. Run _cython_setup.sh in ./plants/data_cython/.
4. Run run_pre.py in ./plants/ for required plant.

To fine-tune a pretrained model, you need to:

1. Run run_epoch.py in ./plants/ with --pre_training. The pretrained models are saved in ./plants/pre/.

Experimental Results

Plant	A.thaliana	B.distachyon	O.sativa-MH	O.sativa-ZS	S.italica	S.bicolor	Z.mays
CDIL w/ pretrain	92.90	93.47	93.53	93.09	94.43	96.42	97.21
CDIL w/o pretrain	90.39	91.95	91.45	91.66	92.42	95.80	95.87
CNN	82.02	87.09	86.05	84.94	88.30	91.52	89.79
PlantDeepSEA	90.24	90.59	91.08	90.18	92.39	94.86	95.19
Transformer	76.74	85.63	83.17	83.56	86.27	88.90	84.78
Nyströmformer w/ pretrain	89.80	92.24	90.75	90.50	92.75	95.45	95.20
Nyströmformer w/o pretrain	86.02	90.19	86.92	86.31	90.94	93.67	89.77
Performer	75.95	85.25	82.81	83.02	86.60	88.09	85.13

cdildna's Issues

Can't find config.yaml file

When run classify_lightning.py to fine-tune a pretrained model, it also need config.yaml file in this script.
Could you please provide this file? or give some revision for classify_lightning.py.
Thank you!