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https://github.com/clemsciences/sequence_alignment

Sequence alignment algorithms
https://github.com/clemsciences/sequence_alignment

alignment sequence-alignment

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Sequence alignment algorithms

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# Sequence alignment

[deterministic_alignment.py](https://github.com/clemsciences/sequence_alignment/blob/master/deterministic_alignment.py)
- Needleman-Wunsch algorithm: global alignment
- Smith-Waterman algorithm: local alignment
- Levenshtein distance: minimum number of operations (insertion, deletion, modification) to transform one sequence to an other sequence

[phmm.py](https://github.com/clemsciences/sequence_alignment/blob/master/phmm.py) : Pair Hidden Markov Model implementation

[blast.py](https://github.com/clemsciences/sequence_alignment/blob/master/blast.py) : heuristics to find local alignments in very long chains

[main.py](https://github.com/clemsciences/sequence_alignment/blob/master/main.py) : examples of presented algorithms

[data_retrieval.py](https://github.com/clemsciences/sequence_alignment/blob/master/data_retrieval.py) : word retrieval thanks to nltk

1. Install nltk with # apt-get install nltk
2. Download Swadesh corpus with
```python
>>> import nltk
>>> nltk.download()
```

[utils.py](https://github.com/clemsciences/sequence_alignment/blob/master/utils.py) : some useful functions which are unclassified

TODO: learning to align pairs of sequences with a Pair Hidden Markov Model.