#SSW: A Python Wrapper for the SIMD Smith-Waterman
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 CPU level. This repository wraps the SSW library into an easy to install, high-level python interface with no external library dependancies.
The SSW library is written by Mengyao Zhao and Wan-Ping Lee, and this python interface is maintained by Giles Hall.
To install the SSW python package, use pip:
$ pip install ssw
import ssw
aligner = ssw.Aligner()
alignment = aligner.align(reference="ACGTGAGAATTATGGCGCTGTGATT", query="ACGTGAGAATTATGCGCTGTGATT")
print(alignment.alignment_report())
Score = 45, Matches = 24, Mismatches = 0, Insertions = 0, Deletions = 1
ref 1 ACGTGAGAATTATGGCGCTGTGATT
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query 1 ACGTGAGAATTAT-GCGCTGTGATT