Package Bio :: Module pairwise2
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Module pairwise2

source code

This package implements pairwise sequence alignment using a dynamic programming algorithm.

This provides functions to get global and local alignments between two sequences. A global alignment finds the best concordance between all characters in two sequences. A local alignment finds just the subsequences that align the best.

When doing alignments, you can specify the match score and gap penalties. The match score indicates the compatibility between an alignment of two characters in the sequences. Highly compatible characters should be given positive scores, and incompatible ones should be given negative scores or 0. The gap penalties should be negative.

The names of the alignment functions in this module follow the convention <alignment type>XX where <alignment type> is either "global" or "local" and XX is a 2 character code indicating the parameters it takes. The first character indicates the parameters for matches (and mismatches), and the second indicates the parameters for gap penalties.

The match parameters are:

x     No parameters. Identical characters have score of 1, otherwise 0.
m     A match score is the score of identical chars, otherwise mismatch
d     A dictionary returns the score of any pair of characters.
c     A callback function returns scores.

The gap penalty parameters are:

x     No gap penalties.
s     Same open and extend gap penalties for both sequences.
d     The sequences have different open and extend gap penalties.
c     A callback function returns the gap penalties.

All the different alignment functions are contained in an object align. For example:

>>> from Bio import pairwise2
>>> alignments = pairwise2.align.globalxx("ACCGT", "ACG")

will return a list of the alignments between the two strings. For a nice printout, use the format_alignment method of the module:

>>> from Bio.pairwise2 import format_alignment
>>> print(format_alignment(*alignments[0]))

All alignment functions have the following arguments:

The other parameters of the alignment function depend on the function called. Some examples:

To see a description of the parameters for a function, please look at the docstring for the function via the help function, e.g. type help(pairwise2.align.localds) at the Python prompt.

Classes [hide private]
identity_match([match][, mismatch]) -> match_fn
dictionary_match(score_dict[, symmetric]) -> match_fn
affine_penalty(open, extend[, penalize_extend_when_opening]) -> gap_fn
Functions [hide private]
_align(sequenceA, sequenceB, match_fn, gap_A_fn, gap_B_fn, penalize_extend_when_opening, penalize_end_gaps, align_globally, gap_char, force_generic, score_only, one_alignment_only)
Return a list of alignments between two sequences or its score
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_make_score_matrix_generic(sequenceA, sequenceB, match_fn, gap_A_fn, gap_B_fn, penalize_end_gaps, align_globally, score_only)
Generate a score and traceback matrix according to Needleman-Wunsch
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_recover_alignments(sequenceA, sequenceB, starts, score_matrix, trace_matrix, align_globally, gap_char, one_alignment_only, gap_A_fn, gap_B_fn)
Do the backtracing and return a list of alignments
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_find_start(score_matrix, align_globally)
Return a list of starting points (score, (row, col)).
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Take a list of alignments and return a cleaned version.
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_finish_backtrace(sequenceA, sequenceB, ali_seqA, ali_seqB, row, col, gap_char)
Add remaining sequences and fill with gaps if neccessary
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_find_gap_open(sequenceA, sequenceB, ali_seqA, ali_seqB, end, row, col, col_gap, gap_char, score_matrix, trace_matrix, in_process, gap_fn, target, index, direction)
Find the starting point(s) of the extended gap
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calc_affine_penalty(length, open, extend, penalize_extend_when_opening) source code
Print out a matrix.
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format_alignment(align1, align2, score, begin, end)
Format the alignment prettily into a string.
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Variables [hide private]
  align = align()
  _PRECISION = 1000
  __package__ = 'Bio'
Function Details [hide private]

_make_score_matrix_generic(sequenceA, sequenceB, match_fn, gap_A_fn, gap_B_fn, penalize_end_gaps, align_globally, score_only)

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Generate a score and traceback matrix according to Needleman-Wunsch

This implementation allows the usage of general gap functions and is rather slow. It is automatically called if you define your own gap functions. You can force the usage of this method with force_generic=True.

_find_start(score_matrix, align_globally)

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Return a list of starting points (score, (row, col)).

Indicating every possible place to start the tracebacks.


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Print out a matrix. For debugging purposes.