- Clone the repo
git clone https://github.com/qinyunnn/TransDNA.git
- Install Conda: please see https://docs.conda.io/en/latest/miniconda.html
- Create Conda env:
conda create -n TransDNA python==3.8
conda activate TransDNA
pip install -r requirements.txt
We provided a training example in examples.
# put your dataset under data/ directory with the same structure shown in the example/data/
data
source_data
|-reads.txt
|-reference.txt
target_data
|-reads.txt
|-reference.txt
- In reads.txt, the adjacent two clusters are segmented using '==============================='. For example:
AACCAATACCTTGAACCTAACTCGAGTTAACAAACGCAATTCACAGAACAAGGACGTCGGACGGTGTCCAGAATACCGGCCTCGTGACCGTGGCCAGGGAACCTGACAATGTCAGGCCTTACCGACACACGCAACCTCTTGCTGAAAGGCCT
AACCAATACCTTGAACCTAACTCGAGTTAACAAACGCAATTCACAGAACAAGGACGTCGGACGGTGTCCAGAATACCGGCCTCGTGACCGTGGCCAGGGAACCTGACAATGTCAGGCCTTACCGACAACGCAACCTCTTGCTGAAAGGCCT
AACCAATACCTTGAACCTAACTCGAGTTAACAAACGCAATTCACAGAACAAGGACGTCGGACGGTGTCCAGAATACCGGCCTCGTGACCGTGGCCAGGGAACCTGACAATGTCAGGCCTTACCGACACACGCAACCTCTTGCTGAAAGGCCT
AACCAATACCTTGAACCTAACTCGAGTTAACAAACGCAATTCACAGAACAAGGACGTCGGACGGTGTCCAGAATACCGGCCTCGTGACCGTGGCCAGGGAACCTGACAATGTCAGGCCTTACCGACACACGCAACCTCTTGCTGAAAGGCCT
===============================
AATACCTTGAAGTCACTGGTACTGAACATGCCTTCTGACCGTTAGGACTTATCTTCCTGTCGGTATAAGATCTACTACTACAACACTGGTTTCAACTAGCGGGAGAAGTCCTTACCGAGTTCTGCGGCTGGCTGATAGCGTGTGCCCTCTGG
AATACCTTGAAGTCACTGGTACTGAACATGCCTTCTGACCGTTAGGACTTATCTTCCTGTCGGTATAAGATCTACTACTACAACACTGGTTTCAACTAGCGGGAGAAGTCCTTACCGAGTTCTGCGGCTGGCTGATAGCGTGTGCCCTCTGG
AATACCTTGAAGTCACTGGTACTGAACATGCCTTCTGACCGTTAGGACTTATCTTCCTGTCGGTATAAGATCTACTACTACAACACTGGTTTCAACTAGCGGGAGAAGTCCTTACCGAGTTCTGCGGCTGGCTGATAGCGTGTGCCCTCTGG
===============================
- First, you can train the source domain with run_source.sh to obtain the pre-trained encoder and decoder.
cd examples
bash run_source.sh
- Then, transfer learning is performed using run_target.sh.
bash run_target.sh
You can change running parameters in run_source.sh and run_target.sh.