This is derived from: original source repository
Please cite this PLOS ONE paper by Zhao et al. 2013
SSW is a fast implementation of the Smith-Waterman algorithm, which uses the Single-Instruction Multiple-Data (SIMD) instructions to parallelize the algorithm at the instruction level. It can return the Smith-Waterman score, alignment location and traceback path (cigar) of the optimal alignment accurately; and return the sub-optimal alignment score and location heuristically.
Note: When SSW open a gap, the gap open penalty alone is applied.
from PyPi
pip install ssw-py
or from source
python setup.py install