A Comparative study of DNA Alignment Algorithms and Boosting Performance Using Different Compilation Strategies
Abstract
With the development of next generation sequencing technologies, the requirement of higher performance from DNA and Protein sequence alignment algorithms has become even greater. This work is a systematic comparison of different compilation strategies for two common DNA or Protein sequence alignment algorithms, Needleman-Wunsch and Smith-Waterman, using Python programming language. It aims to investigate the performance benefits of already widely used Biopython’s pairwise alignment module versus different compilation approaches of an in-house software. It is shown that using Numba just-in-time compiler provide greater performance overall in comparison to PyPy and Cython compilers or the Biopython module. This work may increase the efficiency of software prototyping where large-scale sequence alignment is necessary.
Keywords
DNA/Protein sequence alignment, Python, Just-in-time compilers
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