=========
Alignment
=========

Alignment is a native Python library for generic sequence alignment. It is
useful in cases where your alphabet is arbitrarily large and you cannot use
traditional biological sequence analysis tools. It supports global and local
pairwise sequence alignment. I also plan to add support for profile-profile
alignments, but who knows when.

Usage
=====

Typical usage looks like this::

    from alignment.sequence import Sequence
    from alignment.vocabulary import Vocabulary
    from alignment.sequencealigner import SimpleScoring, GlobalSequenceAligner

    # Create sequences to be aligned.
    a = Sequence('what a beautiful day'.split())
    b = Sequence('what a disappointingly bad day'.split())

    # Create a vocabulary and encode the sequences.
    v = Vocabulary()
    aEncoded = v.encodeSequence(a)
    bEncoded = v.encodeSequence(b)

    # Create a scoring and align the sequences using global aligner.
    scoring = SimpleScoring(2, -1)
    aligner = GlobalSequenceAligner(scoring, -2)
    score, encodeds = aligner.align(aEncoded, bEncoded, backtrace=True)

    # Iterate over optimal alignments and print them.
    for encoded in encodeds:
        alignment = v.decodeSequenceAlignment(encoded)
        print alignment
        print 'Alignment score:', alignment.score
        print 'Percent identity:', alignment.percentIdentity()
        print

TODO List
=========

* Profile-profile alignment is not working yet.

=========
Alignment
=========

Alignment is a native Python library for generic sequence alignment. It is
useful in cases where your alphabet is arbitrarily large and you cannot use
traditional biological sequence analysis tools. It supports global and local
pairwise sequence alignment. I also plan to add support for profile-profile
alignments, but who knows when.

Usage
=====

Typical usage looks like this::

    from alignment.sequence import Sequence
    from alignment.vocabulary import Vocabulary
    from alignment.sequencealigner import SimpleScoring, GlobalSequenceAligner

    # Create sequences to be aligned.
    a = Sequence('what a beautiful day'.split())
    b = Sequence('what a disappointingly bad day'.split())

    # Create a vocabulary and encode the sequences.
    v = Vocabulary()
    aEncoded = v.encodeSequence(a)
    bEncoded = v.encodeSequence(b)

    # Create a scoring and align the sequences using global aligner.
    scoring = SimpleScoring(2, -1)
    aligner = GlobalSequenceAligner(scoring, -2)
    score, encodeds = aligner.align(aEncoded, bEncoded, backtrace=True)

    # Iterate over optimal alignments and print them.
    for encoded in encodeds:
        alignment = v.decodeSequenceAlignment(encoded)
        print alignment
        print 'Alignment score:', alignment.score
        print 'Percent identity:', alignment.percentIdentity()
        print

TODO List
=========

- Profile-profile alignment is not working yet.

Fix the bullet list in readme file.
Fix the bullet list in readme file.
