https://github.com/odoluca/fast-nw-and-sw-pairwise-alignment-using-numba-jit

This project includes Needleman-Wunsch and Smith-Waterman algorithms and their afine gap variations (Gotoh) written to work with Cython, PyPy and Numba. Numba JIT shows greater performance. For Best performance use gotoh_jit.py to get only the best score and use gotoh_jit_traceback to get the best alignment
https://github.com/odoluca/fast-nw-and-sw-pairwise-alignment-using-numba-jit

alignment cython dna-sequences gotoh needleman-wunsch numba pairwise pairwise-alignment protein-sequences pypy3 python python-3-6 smith-waterman

Last synced: 7 months ago
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This project includes Needleman-Wunsch and Smith-Waterman algorithms and their afine gap variations (Gotoh) written to work with Cython, PyPy and Numba. Numba JIT shows greater performance. For Best performance use gotoh_jit.py to get only the best score and use gotoh_jit_traceback to get the best alignment

• Host: GitHub
• URL: https://github.com/odoluca/fast-nw-and-sw-pairwise-alignment-using-numba-jit
• Owner: odoluca
• Created: 2019-07-25T21:43:54.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-09-22T10:20:50.000Z (about 4 years ago)
• Last Synced: 2025-03-25T13:14:55.712Z (7 months ago)
• Topics: alignment, cython, dna-sequences, gotoh, needleman-wunsch, numba, pairwise, pairwise-alignment, protein-sequences, pypy3, python, python-3-6, smith-waterman
• Language: Python
• Homepage:
• Size: 232 KB
• Stars: 2
• Watchers: 0
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Fast-NW-and-SW-Pairwise-alignment-using-numba-JIT

This project includes Needleman-Wunsch and Smith-Waterman algorithms and their afine gap variations (Gotoh) written to work with Cython, PyPy and Numba. Numba JIT shows greater performance and requires Numpy module. Should you not have Numba, remove the "@jit()" decorations and numba import. PyPy and Cython works best with pairwise_standard.py.

For Best performance use pairwise_jit.py.

"local" is for Smith-Waterman algorithm. "global" is for Needleman-Wunsch.

method name extentions:

 

"ms": same match/mismatch scores for all residues. seperate gap open/extend penalties

"ds": uses a substitution matrix for different mismatch penalties between different residues. seperate gap open/extend penalties

  

"_align": report an alignment of sequences. If not used, it returns only the best score. (best score is useful for construction of distance matrix and phylogenetic tree construction)

  

 ===The use example for pairwise_JIT.py===

 

>>>a=convert_to_numeric("ATCTAGTCA")

>>>

>>>b=convert_to_numeric("ATCTAGTCACGTAG")

>>>

>>>res=globalms_align(a,b,1,-1,-1,-2)

>>>

>>>res

>>>

(array([ 1,  0,  3,  0,  1,  2,  0,  3,  1, -1, -1, -1, -1, -1], dtype=int64), array([1, 0, 3, 0, 1, 2, 0, 3, 1, 3, 2, 0, 1, 2], dtype=int64), 4.0)>>>report_alignment(res)

>>>report_alignment(res)

>>>

ATCTAGTCA-----

ATCTAGTCACGTAG

 score: 4.0

 

 ===The use example for pairwise_standard.py=== !SLOWER!

 

>>>a="ATCTAGTCA"

>>>

>>>b="ATCTAGTCACGTAG"

>>>

>>>res=globalms_align(a,b,1,-1,-1,-2)

>>>

>>>res

>>>

(['A', 'T', 'C', 'T', 'A', 'G', 'T', 'C', 'A', -1, -1, -1, -1, -1], ['A', 'T', 'C', 'T', 'A', 'G', 'T', 'C', 'A', 'C', 'G', 'T', 'A', 'G'], 4)

>>>report_alignment(res)

>>>

ATCTAGTCA-----

ATCTAGTCACGTAG

 score: 4.0