AsMac

demo code of AsMac Algorithm

1. preparing training and testing data

Download C++ library SeqAn Or use the attached version:

unzip seqan.zip

Compile the c++ code in folder CppAlign.

cd CppAlign
g++ -I "seqan_library_dir" -std=c++1z -o align main.cpp read_fasta.cpp

Then generate alignment distance result for the input sequences.

./align ../data/training_seq.fa 0

This might cost more than 1 day. The demo code use the finished result: training_dist_prepared.txt

cd ..
python setup_softnw.py build_ext --inplace

This will compile the _softnw.pyx file to a .so file. This file is required to run the jupyter-notebook demo

The algorithm demo is written in Python 3.7, model constructed by torch 1.6.0 Simply run the notebook file demo.ipynb

The code is a demo for the Continuous Sequence Matching model introduced in the paper: Predicting Alignment Distances via Continuous Sequence Matching