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PlantAI-dev/tools/interproscan-5.78-109.0/bin/panther/Bio/Align/__init__.py
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# Copyright 2000, 2004 by Brad Chapman.
# Revisions copyright 2010-2013, 2015-2018 by Peter Cock.
# All rights reserved.
#
# This file is part of the Biopython distribution and governed by your
# choice of the "Biopython License Agreement" or the "BSD 3-Clause License".
# Please see the LICENSE file that should have been included as part of this
# package.
"""Code for dealing with sequence alignments.
One of the most important things in this module is the MultipleSeqAlignment
class, used in the Bio.AlignIO module.
"""
from __future__ import print_function
import sys # Only needed to check if we are using Python 2 or 3
from Bio._py3k import raise_from
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord, _RestrictedDict
from Bio import Alphabet
from Bio.Align import _aligners
# Import errors may occur here if a compiled aligners.c file
# (_aligners.pyd or _aligners.so) is missing or if the user is
# importing from within the Biopython source tree, see PR #2007:
# https://github.com/biopython/biopython/pull/2007
class MultipleSeqAlignment(object):
"""Represents a classical multiple sequence alignment (MSA).
By this we mean a collection of sequences (usually shown as rows) which
are all the same length (usually with gap characters for insertions or
padding). The data can then be regarded as a matrix of letters, with well
defined columns.
You would typically create an MSA by loading an alignment file with the
AlignIO module:
>>> from Bio import AlignIO
>>> align = AlignIO.read("Clustalw/opuntia.aln", "clustal")
>>> print(align)
SingleLetterAlphabet() alignment with 7 rows and 156 columns
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273285|gb|AF191659.1|AF191
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273284|gb|AF191658.1|AF191
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273287|gb|AF191661.1|AF191
TATACATAAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273286|gb|AF191660.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273290|gb|AF191664.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273289|gb|AF191663.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273291|gb|AF191665.1|AF191
In some respects you can treat these objects as lists of SeqRecord objects,
each representing a row of the alignment. Iterating over an alignment gives
the SeqRecord object for each row:
>>> len(align)
7
>>> for record in align:
... print("%s %i" % (record.id, len(record)))
...
gi|6273285|gb|AF191659.1|AF191 156
gi|6273284|gb|AF191658.1|AF191 156
gi|6273287|gb|AF191661.1|AF191 156
gi|6273286|gb|AF191660.1|AF191 156
gi|6273290|gb|AF191664.1|AF191 156
gi|6273289|gb|AF191663.1|AF191 156
gi|6273291|gb|AF191665.1|AF191 156
You can also access individual rows as SeqRecord objects via their index:
>>> print(align[0].id)
gi|6273285|gb|AF191659.1|AF191
>>> print(align[-1].id)
gi|6273291|gb|AF191665.1|AF191
And extract columns as strings:
>>> print(align[:, 1])
AAAAAAA
Or, take just the first ten columns as a sub-alignment:
>>> print(align[:, :10])
SingleLetterAlphabet() alignment with 7 rows and 10 columns
TATACATTAA gi|6273285|gb|AF191659.1|AF191
TATACATTAA gi|6273284|gb|AF191658.1|AF191
TATACATTAA gi|6273287|gb|AF191661.1|AF191
TATACATAAA gi|6273286|gb|AF191660.1|AF191
TATACATTAA gi|6273290|gb|AF191664.1|AF191
TATACATTAA gi|6273289|gb|AF191663.1|AF191
TATACATTAA gi|6273291|gb|AF191665.1|AF191
Combining this alignment slicing with alignment addition allows you to
remove a section of the alignment. For example, taking just the first
and last ten columns:
>>> print(align[:, :10] + align[:, -10:])
SingleLetterAlphabet() alignment with 7 rows and 20 columns
TATACATTAAGTGTACCAGA gi|6273285|gb|AF191659.1|AF191
TATACATTAAGTGTACCAGA gi|6273284|gb|AF191658.1|AF191
TATACATTAAGTGTACCAGA gi|6273287|gb|AF191661.1|AF191
TATACATAAAGTGTACCAGA gi|6273286|gb|AF191660.1|AF191
TATACATTAAGTGTACCAGA gi|6273290|gb|AF191664.1|AF191
TATACATTAAGTATACCAGA gi|6273289|gb|AF191663.1|AF191
TATACATTAAGTGTACCAGA gi|6273291|gb|AF191665.1|AF191
Note - This object replaced the older Alignment object defined in module
Bio.Align.Generic but is not fully backwards compatible with it.
Note - This object does NOT attempt to model the kind of alignments used
in next generation sequencing with multiple sequencing reads which are
much shorter than the alignment, and where there is usually a consensus or
reference sequence with special status.
"""
def __init__(self, records, alphabet=None,
annotations=None, column_annotations=None):
"""Initialize a new MultipleSeqAlignment object.
Arguments:
- records - A list (or iterator) of SeqRecord objects, whose
sequences are all the same length. This may be an be an
empty list.
- alphabet - The alphabet for the whole alignment, typically a gapped
alphabet, which should be a super-set of the individual
record alphabets. If omitted, a consensus alphabet is
used.
- annotations - Information about the whole alignment (dictionary).
- column_annotations - Per column annotation (restricted dictionary).
This holds Python sequences (lists, strings, tuples)
whose length matches the number of columns. A typical
use would be a secondary structure consensus string.
You would normally load a MSA from a file using Bio.AlignIO, but you
can do this from a list of SeqRecord objects too:
>>> from Bio.Alphabet import generic_dna
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> from Bio.Align import MultipleSeqAlignment
>>> a = SeqRecord(Seq("AAAACGT", generic_dna), id="Alpha")
>>> b = SeqRecord(Seq("AAA-CGT", generic_dna), id="Beta")
>>> c = SeqRecord(Seq("AAAAGGT", generic_dna), id="Gamma")
>>> align = MultipleSeqAlignment([a, b, c],
... annotations={"tool": "demo"},
... column_annotations={"stats": "CCCXCCC"})
>>> print(align)
DNAAlphabet() alignment with 3 rows and 7 columns
AAAACGT Alpha
AAA-CGT Beta
AAAAGGT Gamma
>>> align.annotations
{'tool': 'demo'}
>>> align.column_annotations
{'stats': 'CCCXCCC'}
"""
if alphabet is not None:
if not isinstance(alphabet, (Alphabet.Alphabet, Alphabet.AlphabetEncoder)):
raise ValueError("Invalid alphabet argument")
self._alphabet = alphabet
else:
# Default while we add sequences, will take a consensus later
self._alphabet = Alphabet.single_letter_alphabet
self._records = []
if records:
self.extend(records)
if alphabet is None:
# No alphabet was given, take a consensus alphabet
self._alphabet = Alphabet._consensus_alphabet(rec.seq.alphabet for
rec in self._records
if rec.seq is not None)
# Annotations about the whole alignment
if annotations is None:
annotations = {}
elif not isinstance(annotations, dict):
raise TypeError("annotations argument should be a dict")
self.annotations = annotations
# Annotations about each colum of the alignment
if column_annotations is None:
column_annotations = {}
# Handle this via the property set function which will validate it
self.column_annotations = column_annotations
def _set_per_column_annotations(self, value):
if not isinstance(value, dict):
raise TypeError("The per-column-annotations should be a "
"(restricted) dictionary.")
# Turn this into a restricted-dictionary (and check the entries)
if len(self):
# Use the standard method to get the length
expected_length = self.get_alignment_length()
self._per_col_annotations = _RestrictedDict(length=expected_length)
self._per_col_annotations.update(value)
else:
# Bit of a problem case... number of columns is undefined
self._per_col_annotations = None
if value:
raise ValueError("Can't set per-column-annotations without an alignment")
def _get_per_column_annotations(self):
if self._per_col_annotations is None:
# This happens if empty at initialisation
if len(self):
# Use the standard method to get the length
expected_length = self.get_alignment_length()
else:
# Should this raise an exception? Compare SeqRecord behaviour...
expected_length = 0
self._per_col_annotations = _RestrictedDict(length=expected_length)
return self._per_col_annotations
column_annotations = property(
fget=_get_per_column_annotations,
fset=_set_per_column_annotations,
doc="""Dictionary of per-letter-annotation for the sequence.""")
def _str_line(self, record, length=50):
"""Return a truncated string representation of a SeqRecord (PRIVATE).
This is a PRIVATE function used by the __str__ method.
"""
if record.seq.__class__.__name__ == "CodonSeq":
if len(record.seq) <= length:
return "%s %s" % (record.seq, record.id)
else:
return "%s...%s %s" \
% (record.seq[:length - 3], record.seq[-3:], record.id)
else:
if len(record.seq) <= length:
return "%s %s" % (record.seq, record.id)
else:
return "%s...%s %s" \
% (record.seq[:length - 6], record.seq[-3:], record.id)
def __str__(self):
"""Return a multi-line string summary of the alignment.
This output is intended to be readable, but large alignments are
shown truncated. A maximum of 20 rows (sequences) and 50 columns
are shown, with the record identifiers. This should fit nicely on a
single screen. e.g.
>>> from Bio.Alphabet import IUPAC, Gapped
>>> from Bio.Align import MultipleSeqAlignment
>>> align = MultipleSeqAlignment([], Gapped(IUPAC.unambiguous_dna, "-"))
>>> align.add_sequence("Alpha", "ACTGCTAGCTAG")
>>> align.add_sequence("Beta", "ACT-CTAGCTAG")
>>> align.add_sequence("Gamma", "ACTGCTAGATAG")
>>> print(align)
Gapped(IUPACUnambiguousDNA(), '-') alignment with 3 rows and 12 columns
ACTGCTAGCTAG Alpha
ACT-CTAGCTAG Beta
ACTGCTAGATAG Gamma
See also the alignment's format method.
"""
rows = len(self._records)
lines = ["%s alignment with %i rows and %i columns"
% (str(self._alphabet), rows, self.get_alignment_length())]
if rows <= 20:
lines.extend(self._str_line(rec) for rec in self._records)
else:
lines.extend(self._str_line(rec) for rec in self._records[:18])
lines.append("...")
lines.append(self._str_line(self._records[-1]))
return "\n".join(lines)
def __repr__(self):
"""Return a representation of the object for debugging.
The representation cannot be used with eval() to recreate the object,
which is usually possible with simple python ojects. For example:
<Bio.Align.MultipleSeqAlignment instance (2 records of length 14,
SingleLetterAlphabet()) at a3c184c>
The hex string is the memory address of the object, see help(id).
This provides a simple way to visually distinguish alignments of
the same size.
"""
# A doctest for __repr__ would be nice, but __class__ comes out differently
# if run via the __main__ trick.
return "<%s instance (%i records of length %i, %s) at %x>" % \
(self.__class__, len(self._records),
self.get_alignment_length(), repr(self._alphabet), id(self))
# This version is useful for doing eval(repr(alignment)),
# but it can be VERY long:
# return "%s(%s, %s)" \
# % (self.__class__, repr(self._records), repr(self._alphabet))
def format(self, format):
"""Return the alignment as a string in the specified file format.
The format should be a lower case string supported as an output
format by Bio.AlignIO (such as "fasta", "clustal", "phylip",
"stockholm", etc), which is used to turn the alignment into a
string.
e.g.
>>> from Bio.Alphabet import IUPAC, Gapped
>>> from Bio.Align import MultipleSeqAlignment
>>> align = MultipleSeqAlignment([], Gapped(IUPAC.unambiguous_dna, "-"))
>>> align.add_sequence("Alpha", "ACTGCTAGCTAG")
>>> align.add_sequence("Beta", "ACT-CTAGCTAG")
>>> align.add_sequence("Gamma", "ACTGCTAGATAG")
>>> print(align.format("fasta"))
>Alpha
ACTGCTAGCTAG
>Beta
ACT-CTAGCTAG
>Gamma
ACTGCTAGATAG
<BLANKLINE>
>>> print(align.format("phylip"))
3 12
Alpha ACTGCTAGCT AG
Beta ACT-CTAGCT AG
Gamma ACTGCTAGAT AG
<BLANKLINE>
For Python 2.6, 3.0 or later see also the built in format() function.
"""
# See also the __format__ added for Python 2.6 / 3.0, PEP 3101
# See also the SeqRecord class and its format() method using Bio.SeqIO
return self.__format__(format)
def __format__(self, format_spec):
"""Return the alignment as a string in the specified file format.
This method supports the python format() function added in
Python 2.6/3.0. The format_spec should be a lower case
string supported by Bio.AlignIO as an output file format.
See also the alignment's format() method.
"""
if format_spec:
from Bio._py3k import StringIO
from Bio import AlignIO
handle = StringIO()
AlignIO.write([self], handle, format_spec)
return handle.getvalue()
else:
# Follow python convention and default to using __str__
return str(self)
def __iter__(self):
"""Iterate over alignment rows as SeqRecord objects.
e.g.
>>> from Bio.Alphabet import IUPAC, Gapped
>>> from Bio.Align import MultipleSeqAlignment
>>> align = MultipleSeqAlignment([], Gapped(IUPAC.unambiguous_dna, "-"))
>>> align.add_sequence("Alpha", "ACTGCTAGCTAG")
>>> align.add_sequence("Beta", "ACT-CTAGCTAG")
>>> align.add_sequence("Gamma", "ACTGCTAGATAG")
>>> for record in align:
... print(record.id)
... print(record.seq)
...
Alpha
ACTGCTAGCTAG
Beta
ACT-CTAGCTAG
Gamma
ACTGCTAGATAG
"""
return iter(self._records)
def __len__(self):
"""Return the number of sequences in the alignment.
Use len(alignment) to get the number of sequences (i.e. the number of
rows), and alignment.get_alignment_length() to get the length of the
longest sequence (i.e. the number of columns).
This is easy to remember if you think of the alignment as being like a
list of SeqRecord objects.
"""
return len(self._records)
def get_alignment_length(self):
"""Return the maximum length of the alignment.
All objects in the alignment should (hopefully) have the same
length. This function will go through and find this length
by finding the maximum length of sequences in the alignment.
>>> from Bio.Alphabet import IUPAC, Gapped
>>> from Bio.Align import MultipleSeqAlignment
>>> align = MultipleSeqAlignment([], Gapped(IUPAC.unambiguous_dna, "-"))
>>> align.add_sequence("Alpha", "ACTGCTAGCTAG")
>>> align.add_sequence("Beta", "ACT-CTAGCTAG")
>>> align.add_sequence("Gamma", "ACTGCTAGATAG")
>>> align.get_alignment_length()
12
If you want to know the number of sequences in the alignment,
use len(align) instead:
>>> len(align)
3
"""
max_length = 0
for record in self._records:
if len(record.seq) > max_length:
max_length = len(record.seq)
return max_length
def add_sequence(self, descriptor, sequence, start=None, end=None,
weight=1.0):
"""Add a sequence to the alignment.
This doesn't do any kind of alignment, it just adds in the sequence
object, which is assumed to be prealigned with the existing
sequences.
Arguments:
- descriptor - The descriptive id of the sequence being added.
This will be used as the resulting SeqRecord's
.id property (and, for historical compatibility,
also the .description property)
- sequence - A string with sequence info.
- start - You can explicitly set the start point of the sequence.
This is useful (at least) for BLAST alignments, which can
just be partial alignments of sequences.
- end - Specify the end of the sequence, which is important
for the same reason as the start.
- weight - The weight to place on the sequence in the alignment.
By default, all sequences have the same weight. (0.0 =>
no weight, 1.0 => highest weight)
In general providing a SeqRecord and calling .append is preferred.
"""
new_seq = Seq(sequence, self._alphabet)
# We are now effectively using the SeqRecord's .id as
# the primary identifier (e.g. in Bio.SeqIO) so we should
# populate it with the descriptor.
# For backwards compatibility, also store this in the
# SeqRecord's description property.
new_record = SeqRecord(new_seq,
id=descriptor,
description=descriptor)
# hack! We really need to work out how to deal with annotations
# and features in biopython. Right now, I'll just use the
# generic annotations dictionary we've got to store the start
# and end, but we should think up something better. I don't know
# if I'm really a big fan of the LocatableSeq thing they've got
# in BioPerl, but I'm not positive what the best thing to do on
# this is...
if start:
new_record.annotations["start"] = start
if end:
new_record.annotations["end"] = end
# another hack to add weight information to the sequence
new_record.annotations["weight"] = weight
self._records.append(new_record)
def extend(self, records):
"""Add more SeqRecord objects to the alignment as rows.
They must all have the same length as the original alignment, and have
alphabets compatible with the alignment's alphabet. For example,
>>> from Bio.Alphabet import generic_dna
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> from Bio.Align import MultipleSeqAlignment
>>> a = SeqRecord(Seq("AAAACGT", generic_dna), id="Alpha")
>>> b = SeqRecord(Seq("AAA-CGT", generic_dna), id="Beta")
>>> c = SeqRecord(Seq("AAAAGGT", generic_dna), id="Gamma")
>>> d = SeqRecord(Seq("AAAACGT", generic_dna), id="Delta")
>>> e = SeqRecord(Seq("AAA-GGT", generic_dna), id="Epsilon")
First we create a small alignment (three rows):
>>> align = MultipleSeqAlignment([a, b, c])
>>> print(align)
DNAAlphabet() alignment with 3 rows and 7 columns
AAAACGT Alpha
AAA-CGT Beta
AAAAGGT Gamma
Now we can extend this alignment with another two rows:
>>> align.extend([d, e])
>>> print(align)
DNAAlphabet() alignment with 5 rows and 7 columns
AAAACGT Alpha
AAA-CGT Beta
AAAAGGT Gamma
AAAACGT Delta
AAA-GGT Epsilon
Because the alignment object allows iteration over the rows as
SeqRecords, you can use the extend method with a second alignment
(provided its sequences have the same length as the original alignment).
"""
if len(self):
# Use the standard method to get the length
expected_length = self.get_alignment_length()
else:
# Take the first record's length
records = iter(records) # records arg could be list or iterator
try:
rec = next(records)
except StopIteration:
# Special case, no records
return
expected_length = len(rec)
self._append(rec, expected_length)
# Can now setup the per-column-annotations as well, set to None
# while missing the length:
self.column_annotations = {}
# Now continue to the rest of the records as usual
for rec in records:
self._append(rec, expected_length)
def append(self, record):
"""Add one more SeqRecord object to the alignment as a new row.
This must have the same length as the original alignment (unless this is
the first record), and have an alphabet compatible with the alignment's
alphabet.
>>> from Bio import AlignIO
>>> align = AlignIO.read("Clustalw/opuntia.aln", "clustal")
>>> print(align)
SingleLetterAlphabet() alignment with 7 rows and 156 columns
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273285|gb|AF191659.1|AF191
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273284|gb|AF191658.1|AF191
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273287|gb|AF191661.1|AF191
TATACATAAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273286|gb|AF191660.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273290|gb|AF191664.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273289|gb|AF191663.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273291|gb|AF191665.1|AF191
>>> len(align)
7
We'll now construct a dummy record to append as an example:
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> dummy = SeqRecord(Seq("N"*156), id="dummy")
Now append this to the alignment,
>>> align.append(dummy)
>>> print(align)
SingleLetterAlphabet() alignment with 8 rows and 156 columns
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273285|gb|AF191659.1|AF191
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273284|gb|AF191658.1|AF191
TATACATTAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273287|gb|AF191661.1|AF191
TATACATAAAAGAAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273286|gb|AF191660.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273290|gb|AF191664.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273289|gb|AF191663.1|AF191
TATACATTAAAGGAGGGGGATGCGGATAAATGGAAAGGCGAAAG...AGA gi|6273291|gb|AF191665.1|AF191
NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN...NNN dummy
>>> len(align)
8
"""
if self._records:
self._append(record, self.get_alignment_length())
else:
self._append(record)
def _append(self, record, expected_length=None):
"""Validate and append a record (PRIVATE)."""
if not isinstance(record, SeqRecord):
raise TypeError("New sequence is not a SeqRecord object")
# Currently the get_alignment_length() call is expensive, so we need
# to avoid calling it repeatedly for __init__ and extend, hence this
# private _append method
if expected_length is not None and len(record) != expected_length:
# TODO - Use the following more helpful error, but update unit tests
# raise ValueError("New sequence is not of length %i" \
# % self.get_alignment_length())
raise ValueError("Sequences must all be the same length")
# Using not self.alphabet.contains(record.seq.alphabet) needs fixing
# for AlphabetEncoders (e.g. gapped versus ungapped).
if not Alphabet._check_type_compatible([self._alphabet, record.seq.alphabet]):
raise ValueError("New sequence's alphabet is incompatible")
self._records.append(record)
def __add__(self, other):
"""Combine two alignments with the same number of rows by adding them.
If you have two multiple sequence alignments (MSAs), there are two ways to think
about adding them - by row or by column. Using the extend method adds by row.
Using the addition operator adds by column. For example,
>>> from Bio.Alphabet import generic_dna
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> from Bio.Align import MultipleSeqAlignment
>>> a1 = SeqRecord(Seq("AAAAC", generic_dna), id="Alpha")
>>> b1 = SeqRecord(Seq("AAA-C", generic_dna), id="Beta")
>>> c1 = SeqRecord(Seq("AAAAG", generic_dna), id="Gamma")
>>> a2 = SeqRecord(Seq("GT", generic_dna), id="Alpha")
>>> b2 = SeqRecord(Seq("GT", generic_dna), id="Beta")
>>> c2 = SeqRecord(Seq("GT", generic_dna), id="Gamma")
>>> left = MultipleSeqAlignment([a1, b1, c1],
... annotations={"tool": "demo", "name": "start"},
... column_annotations={"stats": "CCCXC"})
>>> right = MultipleSeqAlignment([a2, b2, c2],
... annotations={"tool": "demo", "name": "end"},
... column_annotations={"stats": "CC"})
Now, let's look at these two alignments:
>>> print(left)
DNAAlphabet() alignment with 3 rows and 5 columns
AAAAC Alpha
AAA-C Beta
AAAAG Gamma
>>> print(right)
DNAAlphabet() alignment with 3 rows and 2 columns
GT Alpha
GT Beta
GT Gamma
And add them:
>>> combined = left + right
>>> print(combined)
DNAAlphabet() alignment with 3 rows and 7 columns
AAAACGT Alpha
AAA-CGT Beta
AAAAGGT Gamma
For this to work, both alignments must have the same number of records (here
they both have 3 rows):
>>> len(left)
3
>>> len(right)
3
>>> len(combined)
3
The individual rows are SeqRecord objects, and these can be added together. Refer
to the SeqRecord documentation for details of how the annotation is handled. This
example is a special case in that both original alignments shared the same names,
meaning when the rows are added they also get the same name.
Any common annotations are preserved, but differing annotation is lost. This is
the same behaviour used in the SeqRecord annotations and is designed to prevent
accidental propagation of inappropriate values:
>>> combined.annotations
{'tool': 'demo'}
Similarly any common per-column-annotations are combined:
>>> combined.column_annotations
{'stats': 'CCCXCCC'}
"""
if not isinstance(other, MultipleSeqAlignment):
raise NotImplementedError
if len(self) != len(other):
raise ValueError("When adding two alignments they must have the same length"
" (i.e. same number or rows)")
alpha = Alphabet._consensus_alphabet([self._alphabet, other._alphabet])
merged = (left + right for left, right in zip(self, other))
# Take any common annotation:
annotations = {}
for k, v in self.annotations.items():
if k in other.annotations and other.annotations[k] == v:
annotations[k] = v
column_annotations = {}
for k, v in self.column_annotations.items():
if k in other.column_annotations:
column_annotations[k] = v + other.column_annotations[k]
return MultipleSeqAlignment(merged, alpha, annotations, column_annotations)
def __getitem__(self, index):
"""Access part of the alignment.
Depending on the indices, you can get a SeqRecord object
(representing a single row), a Seq object (for a single columns),
a string (for a single characters) or another alignment
(representing some part or all of the alignment).
align[r,c] gives a single character as a string
align[r] gives a row as a SeqRecord
align[r,:] gives a row as a SeqRecord
align[:,c] gives a column as a Seq (using the alignment's alphabet)
align[:] and align[:,:] give a copy of the alignment
Anything else gives a sub alignment, e.g.
align[0:2] or align[0:2,:] uses only row 0 and 1
align[:,1:3] uses only columns 1 and 2
align[0:2,1:3] uses only rows 0 & 1 and only cols 1 & 2
We'll use the following example alignment here for illustration:
>>> from Bio.Alphabet import generic_dna
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> from Bio.Align import MultipleSeqAlignment
>>> a = SeqRecord(Seq("AAAACGT", generic_dna), id="Alpha")
>>> b = SeqRecord(Seq("AAA-CGT", generic_dna), id="Beta")
>>> c = SeqRecord(Seq("AAAAGGT", generic_dna), id="Gamma")
>>> d = SeqRecord(Seq("AAAACGT", generic_dna), id="Delta")
>>> e = SeqRecord(Seq("AAA-GGT", generic_dna), id="Epsilon")
>>> align = MultipleSeqAlignment([a, b, c, d, e], generic_dna)
You can access a row of the alignment as a SeqRecord using an integer
index (think of the alignment as a list of SeqRecord objects here):
>>> first_record = align[0]
>>> print("%s %s" % (first_record.id, first_record.seq))
Alpha AAAACGT
>>> last_record = align[-1]
>>> print("%s %s" % (last_record.id, last_record.seq))
Epsilon AAA-GGT
You can also access use python's slice notation to create a sub-alignment
containing only some of the SeqRecord objects:
>>> sub_alignment = align[2:5]
>>> print(sub_alignment)
DNAAlphabet() alignment with 3 rows and 7 columns
AAAAGGT Gamma
AAAACGT Delta
AAA-GGT Epsilon
This includes support for a step, i.e. align[start:end:step], which
can be used to select every second sequence:
>>> sub_alignment = align[::2]
>>> print(sub_alignment)
DNAAlphabet() alignment with 3 rows and 7 columns
AAAACGT Alpha
AAAAGGT Gamma
AAA-GGT Epsilon
Or to get a copy of the alignment with the rows in reverse order:
>>> rev_alignment = align[::-1]
>>> print(rev_alignment)
DNAAlphabet() alignment with 5 rows and 7 columns
AAA-GGT Epsilon
AAAACGT Delta
AAAAGGT Gamma
AAA-CGT Beta
AAAACGT Alpha
You can also use two indices to specify both rows and columns. Using simple
integers gives you the entry as a single character string. e.g.
>>> align[3, 4]
'C'
This is equivalent to:
>>> align[3][4]
'C'
or:
>>> align[3].seq[4]
'C'
To get a single column (as a string) use this syntax:
>>> align[:, 4]
'CCGCG'
Or, to get part of a column,
>>> align[1:3, 4]
'CG'
However, in general you get a sub-alignment,
>>> print(align[1:5, 3:6])
DNAAlphabet() alignment with 4 rows and 3 columns
-CG Beta
AGG Gamma
ACG Delta
-GG Epsilon
This should all seem familiar to anyone who has used the NumPy
array or matrix objects.
"""
if isinstance(index, int):
# e.g. result = align[x]
# Return a SeqRecord
return self._records[index]
elif isinstance(index, slice):
# e.g. sub_align = align[i:j:k]
new = MultipleSeqAlignment(self._records[index], self._alphabet)
if self.column_annotations and len(new) == len(self):
# All rows kept (although could have been reversed)
# Perserve the column annotations too,
for k, v in self.column_annotations.items():
new.column_annotations[k] = v
return new
elif len(index) != 2:
raise TypeError("Invalid index type.")
# Handle double indexing
row_index, col_index = index
if isinstance(row_index, int):
# e.g. row_or_part_row = align[6, 1:4], gives a SeqRecord
return self._records[row_index][col_index]
elif isinstance(col_index, int):
# e.g. col_or_part_col = align[1:5, 6], gives a string
return "".join(rec[col_index] for rec in self._records[row_index])
else:
# e.g. sub_align = align[1:4, 5:7], gives another alignment
new = MultipleSeqAlignment((rec[col_index] for rec in self._records[row_index]),
self._alphabet)
if self.column_annotations and len(new) == len(self):
# All rows kept (although could have been reversed)
# Perserve the column annotations too,
for k, v in self.column_annotations.items():
new.column_annotations[k] = v[col_index]
return new
def sort(self, key=None, reverse=False):
"""Sort the rows (SeqRecord objects) of the alignment in place.
This sorts the rows alphabetically using the SeqRecord object id by
default. The sorting can be controlled by supplying a key function
which must map each SeqRecord to a sort value.
This is useful if you want to add two alignments which use the same
record identifiers, but in a different order. For example,
>>> from Bio.Alphabet import generic_dna
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> from Bio.Align import MultipleSeqAlignment
>>> align1 = MultipleSeqAlignment([
... SeqRecord(Seq("ACGT", generic_dna), id="Human"),
... SeqRecord(Seq("ACGG", generic_dna), id="Mouse"),
... SeqRecord(Seq("ACGC", generic_dna), id="Chicken"),
... ])
>>> align2 = MultipleSeqAlignment([
... SeqRecord(Seq("CGGT", generic_dna), id="Mouse"),
... SeqRecord(Seq("CGTT", generic_dna), id="Human"),
... SeqRecord(Seq("CGCT", generic_dna), id="Chicken"),
... ])
If you simple try and add these without sorting, you get this:
>>> print(align1 + align2)
DNAAlphabet() alignment with 3 rows and 8 columns
ACGTCGGT <unknown id>
ACGGCGTT <unknown id>
ACGCCGCT Chicken
Consult the SeqRecord documentation which explains why you get a
default value when annotation like the identifier doesn't match up.
However, if we sort the alignments first, then add them we get the
desired result:
>>> align1.sort()
>>> align2.sort()
>>> print(align1 + align2)
DNAAlphabet() alignment with 3 rows and 8 columns
ACGCCGCT Chicken
ACGTCGTT Human
ACGGCGGT Mouse
As an example using a different sort order, you could sort on the
GC content of each sequence.
>>> from Bio.SeqUtils import GC
>>> print(align1)
DNAAlphabet() alignment with 3 rows and 4 columns
ACGC Chicken
ACGT Human
ACGG Mouse
>>> align1.sort(key = lambda record: GC(record.seq))
>>> print(align1)
DNAAlphabet() alignment with 3 rows and 4 columns
ACGT Human
ACGC Chicken
ACGG Mouse
There is also a reverse argument, so if you wanted to sort by ID
but backwards:
>>> align1.sort(reverse=True)
>>> print(align1)
DNAAlphabet() alignment with 3 rows and 4 columns
ACGG Mouse
ACGT Human
ACGC Chicken
"""
if key is None:
self._records.sort(key=lambda r: r.id, reverse=reverse)
else:
self._records.sort(key=key, reverse=reverse)
class PairwiseAlignment(object):
"""Represents a pairwise sequence alignment.
Internally, the pairwise alignment is stored as the path through
the traceback matrix, i.e. a tuple of pairs of indices corresponding
to the vertices of the path in the traceback matrix.
"""
def __init__(self, target, query, path, score):
"""Initialize a new PairwiseAlignment object.
Arguments:
- target - The first sequence, as a plain string, without gaps.
- query - The second sequence, as a plain string, without gaps.
- path - The path through the traceback matrix, defining an
alignment.
- score - The alignment score.
You would normally obtain a PairwiseAlignment object by iterating
over a PairwiseAlignments object.
"""
self.target = target
self.query = query
self.score = score
self.path = path
# For Python2 only
def __cmp__(self, other):
if self.path < other.path:
return -1
if self.path > other.path:
return +1
return 0
def __eq__(self, other):
return self.path == other.path
def __ne__(self, other):
return self.path != other.path
def __lt__(self, other):
return self.path < other.path
def __le__(self, other):
return self.path <= other.path
def __gt__(self, other):
return self.path > other.path
def __ge__(self, other):
return self.path >= other.path
def __format__(self, format_spec):
if format_spec == "psl":
return self._format_psl()
return str(self)
def __str__(self):
if isinstance(self.query, str) and isinstance(self.target, str):
return self.format()
else:
return self._format_generalized()
def format(self):
"""Create a human-readable representation of the alignment."""
query = self.query
target = self.target
try:
# check if query is a SeqRecord
query = query.seq
except AttributeError:
# query is a Seq object or a plain string
pass
try:
# check if target is a SeqRecord
target = target.seq
except AttributeError:
# target is a Seq object or a plain string
pass
seq1 = str(target)
seq2 = str(query)
n1 = len(seq1)
n2 = len(seq2)
aligned_seq1 = ""
aligned_seq2 = ""
pattern = ""
path = self.path
end1, end2 = path[0]
if end1 > 0 or end2 > 0:
end = max(end1, end2)
aligned_seq1 += " " * (end - end1) + seq1[:end1]
aligned_seq2 += " " * (end - end2) + seq2[:end2]
pattern += " " * end
start1 = end1
start2 = end2
for end1, end2 in path[1:]:
gap = 0
if end1 == start1:
gap = end2 - start2
aligned_seq1 += "-" * gap
aligned_seq2 += seq2[start2:end2]
pattern += "-" * gap
elif end2 == start2:
gap = end1 - start1
aligned_seq1 += seq1[start1:end1]
aligned_seq2 += "-" * gap
pattern += "-" * gap
else:
s1 = seq1[start1:end1]
s2 = seq2[start2:end2]
aligned_seq1 += s1
aligned_seq2 += s2
for c1, c2 in zip(s1, s2):
if c1 == c2:
pattern += "|"
else:
pattern += "."
start1 = end1
start2 = end2
n1 -= end1
n2 -= end2
n = max(n1, n2)
aligned_seq1 += seq1[end1:] + " " * (n - n1)
aligned_seq2 += seq2[end2:] + " " * (n - n2)
pattern += " " * n
return "%s\n%s\n%s\n" % (aligned_seq1, pattern, aligned_seq2)
def _format_generalized(self):
seq1 = self.target
seq2 = self.query
n1 = len(seq1)
n2 = len(seq2)
aligned_seq1 = []
aligned_seq2 = []
pattern = []
path = self.path
end1, end2 = path[0]
if end1 > 0 or end2 > 0:
if end1 <= end2:
for c2 in seq2[:end2 - end1]:
s2 = str(c2)
s1 = " " * len(s2)
aligned_seq1.append(s1)
aligned_seq2.append(s2)
pattern.append(s1)
else: # end1 > end2
for c1 in seq1[:end1 - end2]:
s1 = str(c1)
s2 = " " * len(s1)
aligned_seq1.append(s1)
aligned_seq2.append(s2)
pattern.append(s2)
start1 = end1
start2 = end2
for end1, end2 in path[1:]:
if end1 == start1:
for c2 in seq2[start2:end2]:
s2 = str(c2)
s1 = "-" * len(s2)
aligned_seq1.append(s1)
aligned_seq2.append(s2)
pattern.append(s1)
start2 = end2
elif end2 == start2:
for c1 in seq1[start1:end1]:
s1 = str(c1)
s2 = "-" * len(s1)
aligned_seq1.append(s1)
aligned_seq2.append(s2)
pattern.append(s2)
start1 = end1
else:
for c1, c2 in zip(seq1[start1:end1], seq2[start2:end2]):
s1 = str(c1)
s2 = str(c2)
m1 = len(s1)
m2 = len(s2)
if c1 == c2:
p = "|"
else:
p = "."
if m1 < m2:
space = (m2 - m1) * " "
s1 += space
pattern.append(p * m1 + space)
elif m1 > m2:
space = (m1 - m2) * " "
s2 += space
pattern.append(p * m2 + space)
else:
pattern.append(p * m1)
aligned_seq1.append(s1)
aligned_seq2.append(s2)
start1 = end1
start2 = end2
aligned_seq1 = " ".join(aligned_seq1)
aligned_seq2 = " ".join(aligned_seq2)
pattern = " ".join(pattern)
return "%s\n%s\n%s\n" % (aligned_seq1, pattern, aligned_seq2)
def _format_psl(self):
query = self.query
target = self.target
try:
Qname = query.id
except AttributeError:
Qname = "query"
else:
query = query.seq
try:
Tname = target.id
except AttributeError:
Tname = "target"
else:
target = target.seq
seq1 = str(target)
seq2 = str(query)
n1 = len(seq1)
n2 = len(seq2)
match = 0
mismatch = 0
repmatch = 0
Ns = 0
Qgapcount = 0
Qgapbases = 0
Tgapcount = 0
Tgapbases = 0
Qsize = n2
Qstart = 0
Qend = Qsize
Tsize = n1
Tstart = 0
Tend = Tsize
blockSizes = []
qStarts = []
tStarts = []
strand = "+"
start1 = 0
start2 = 0
start1, start2 = self.path[0]
for end1, end2 in self.path[1:]:
count1 = end1 - start1
count2 = end2 - start2
if count1 == 0:
if start2 == 0:
Qstart += count2
elif end2 == n2:
Qend -= count2
else:
Qgapcount += 1
Qgapbases += count2
start2 = end2
elif count2 == 0:
if start1 == 0:
Tstart += count1
elif end1 == n1:
Tend -= count1
else:
Tgapcount += 1
Tgapbases += count1
start1 = end1
else:
assert count1 == count2
tStarts.append(start1)
qStarts.append(start2)
blockSizes.append(count1)
for c1, c2 in zip(seq1[start1:end1], seq2[start2:end2]):
if c1 == "N" or c2 == "N":
Ns += 1
elif c1 == c2:
match += 1
else:
mismatch += 1
start1 = end1
start2 = end2
blockcount = len(blockSizes)
blockSizes = ",".join(map(str, blockSizes)) + ","
qStarts = ",".join(map(str, qStarts)) + ","
tStarts = ",".join(map(str, tStarts)) + ","
words = [str(match),
str(mismatch),
str(repmatch),
str(Ns),
str(Qgapcount),
str(Qgapbases),
str(Tgapcount),
str(Tgapbases),
strand,
Qname,
str(Qsize),
str(Qstart),
str(Qend),
Tname,
str(Tsize),
str(Tstart),
str(Tend),
str(blockcount),
blockSizes,
qStarts,
tStarts,
]
line = "\t".join(words) + "\n"
return line
@property
def aligned(self):
"""Return the indices of subsequences aligned to each other.
This property returns the start and end indices of subsequences
in the target and query sequence that were aligned to each other.
If the alignment between target (t) and query (q) consists of N
chunks, you get two tuples of length N:
(((t_start1, t_end1), (t_start2, t_end2), ..., (t_startN, t_endN)),
((q_start1, q_end1), (q_start2, q_end2), ..., (q_startN, q_endN)))
For example,
>>> from Bio import Align
>>> aligner = Align.PairwiseAligner()
>>> alignments = aligner.align("GAACT", "GAT")
>>> alignment = alignments[0]
>>> print(alignment)
GAACT
||--|
GA--T
<BLANKLINE>
>>> alignment.aligned
(((0, 2), (4, 5)), ((0, 2), (2, 3)))
>>> alignment = alignments[1]
>>> print(alignment)
GAACT
|-|-|
G-A-T
<BLANKLINE>
>>> alignment.aligned
(((0, 1), (2, 3), (4, 5)), ((0, 1), (1, 2), (2, 3)))
Note that different alignments may have the same subsequences
aligned to each other. In particular, this may occur if alignments
differ from each other in terms of their gap placement only:
>>> aligner.mismatch_score = -10
>>> alignments = aligner.align("AAACAAA", "AAAGAAA")
>>> len(alignments)
2
>>> print(alignments[0])
AAAC-AAA
|||--|||
AAA-GAAA
<BLANKLINE>
>>> alignments[0].aligned
(((0, 3), (4, 7)), ((0, 3), (4, 7)))
>>> print(alignments[1])
AAA-CAAA
|||--|||
AAAG-AAA
<BLANKLINE>
>>> alignments[1].aligned
(((0, 3), (4, 7)), ((0, 3), (4, 7)))
The property can be used to identify alignments that are identical
to each other in terms of their aligned sequences.
"""
segments1 = []
segments2 = []
if sys.version_info[0] > 2:
i1, i2 = self.path[0]
for node in self.path[1:]:
j1, j2 = node
if j1 > i1 and j2 > i2:
segment1 = (i1, j1)
segment2 = (i2, j2)
segments1.append(segment1)
segments2.append(segment2)
i1, i2 = j1, j2
else:
# Python 2: convert all long ints to ints to be consistent
# with the doctests
i1, i2 = self.path[0]
i1 = int(i1)
i2 = int(i2)
for node in self.path[1:]:
j1, j2 = node
j1 = int(j1)
j2 = int(j2)
if j1 > i1 and j2 > i2:
segment1 = (i1, j1)
segment2 = (i2, j2)
segments1.append(segment1)
segments2.append(segment2)
i1, i2 = j1, j2
return tuple(segments1), tuple(segments2)
class PairwiseAlignments(object):
"""Implements an iterator over pairwise alignments returned by the aligner.
This class also supports indexing, which is fast for increasing indices,
but may be slow for random access of a large number of alignments.
Note that pairwise aligners can return an astronomical number of alignments,
even for relatively short sequences, if they align poorly to each other. We
therefore recommend to first check the number of alignments, accessible as
len(alignments), which can be calculated quickly even if the number of
alignments is very large.
"""
def __init__(self, seqA, seqB, score, paths):
"""Initialize a new PairwiseAlignments object.
Arguments:
- seqA - The first sequence, as a plain string, without gaps.
- seqB - The second sequence, as a plain string, without gaps.
- score - The alignment score.
- paths - An iterator over the paths in the traceback matrix;
each path defines one alignment.
You would normally obtain an PairwiseAlignments object by calling
aligner.align(seqA, seqB), where aligner is a PairwiseAligner object.
"""
self.seqA = seqA
self.seqB = seqB
self.score = score
self.paths = paths
self.index = -1
def __len__(self):
return len(self.paths)
def __getitem__(self, index):
if index == self.index:
return self.alignment
if index < self.index:
self.paths.reset()
self.index = -1
while self.index < index:
try:
alignment = next(self)
except StopIteration:
raise_from(IndexError("index out of range"), None)
return alignment
def __iter__(self):
self.paths.reset()
self.index = -1
return self
def __next__(self):
path = next(self.paths)
self.index += 1
alignment = PairwiseAlignment(self.seqA, self.seqB, path, self.score)
self.alignment = alignment
return alignment
if sys.version_info[0] < 3: # Python 2
next = __next__
class PairwiseAligner(_aligners.PairwiseAligner):
"""Performs pairwise sequence alignment using dynamic programming.
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.
To perform a pairwise sequence alignment, first create a PairwiseAligner
object. This object stores the match and mismatch scores, as well as the
gap scores. Typically, match scores are positive, while mismatch scores
and gap scores are negative or zero. By default, the match score is 1,
and the mismatch and gap scores are zero. Based on the values of the gap
scores, a PairwiseAligner object automatically chooses the appropriate
alignment algorithm (the Needleman-Wunsch, Smith-Waterman, Gotoh, or
Waterman-Smith-Beyer global or local alignment algorithm).
Calling the "score" method on the aligner with two sequences as arguments
will calculate the alignment score between the two sequences.
Calling the "align" method on the aligner with two sequences as arguments
will return a generator yielding the alignments between the two
sequences.
Some examples:
>>> from Bio import Align
>>> aligner = Align.PairwiseAligner()
>>> alignments = aligner.align("TACCG", "ACG")
>>> for alignment in sorted(alignments):
... print("Score = %.1f:" % alignment.score)
... print(alignment)
...
Score = 3.0:
TACCG
-|-||
-A-CG
<BLANKLINE>
Score = 3.0:
TACCG
-||-|
-AC-G
<BLANKLINE>
Specify the aligner mode as local to generate local alignments:
>>> aligner.mode = 'local'
>>> alignments = aligner.align("TACCG", "ACG")
>>> for alignment in sorted(alignments):
... print("Score = %.1f:" % alignment.score)
... print(alignment)
...
Score = 3.0:
TACCG
|-||
A-CG
<BLANKLINE>
Score = 3.0:
TACCG
||-|
AC-G
<BLANKLINE>
Do a global alignment. Identical characters are given 2 points,
1 point is deducted for each non-identical character.
>>> aligner.mode = 'global'
>>> aligner.match_score = 2
>>> aligner.mismatch_score = -1
>>> for alignment in aligner.align("TACCG", "ACG"):
... print("Score = %.1f:" % alignment.score)
... print(alignment)
...
Score = 6.0:
TACCG
-||-|
-AC-G
<BLANKLINE>
Score = 6.0:
TACCG
-|-||
-A-CG
<BLANKLINE>
Same as above, except now 0.5 points are deducted when opening a
gap, and 0.1 points are deducted when extending it.
>>> aligner.open_gap_score = -0.5
>>> aligner.extend_gap_score = -0.1
>>> aligner.target_end_gap_score = 0.0
>>> aligner.query_end_gap_score = 0.0
>>> for alignment in aligner.align("TACCG", "ACG"):
... print("Score = %.1f:" % alignment.score)
... print(alignment)
...
Score = 5.5:
TACCG
-|-||
-A-CG
<BLANKLINE>
Score = 5.5:
TACCG
-||-|
-AC-G
<BLANKLINE>
The alignment function can also use known matrices already included in
Biopython:
>>> from Bio.Align import substitution_matrices
>>> aligner = Align.PairwiseAligner()
>>> aligner.substitution_matrix = substitution_matrices.load("BLOSUM62")
>>> alignments = aligner.align("KEVLA", "EVL")
>>> alignments = list(alignments)
>>> print("Number of alignments: %d" % len(alignments))
Number of alignments: 1
>>> alignment = alignments[0]
>>> print("Score = %.1f" % alignment.score)
Score = 13.0
>>> print(alignment)
KEVLA
-|||-
-EVL-
<BLANKLINE>
"""
def __setattr__(self, key, value):
if key not in dir(_aligners.PairwiseAligner):
# To prevent confusion, don't allow users to create new attributes
message = "'PairwiseAligner' object has no attribute '%s'" % key
raise AttributeError(message)
_aligners.PairwiseAligner.__setattr__(self, key, value)
def align(self, seqA, seqB):
"""Return the alignments of two sequences using PairwiseAligner."""
if isinstance(seqA, Seq):
seqA = str(seqA)
if isinstance(seqB, Seq):
seqB = str(seqB)
score, paths = _aligners.PairwiseAligner.align(self, seqA, seqB)
alignments = PairwiseAlignments(seqA, seqB, score, paths)
return alignments
def score(self, seqA, seqB):
"""Return the alignments score of two sequences using PairwiseAligner."""
if isinstance(seqA, Seq):
seqA = str(seqA)
if isinstance(seqB, Seq):
seqB = str(seqB)
return _aligners.PairwiseAligner.score(self, seqA, seqB)
if __name__ == "__main__":
from Bio._utils import run_doctest
run_doctest()
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