# 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.Seq import Seq from Bio.SeqRecord import SeqRecord, _RestrictedDict from Bio import Alphabet try: from Bio.Align import _aligners except ImportError as e: new_exc = ImportError("{}: you should not import directly from the " "biopython source directory; please exit the source " "tree and re-launch your code from there".format(e)) new_exc.__cause__ = None raise new_exc 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: 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 >>> print(align.format("phylip")) 3 12 Alpha ACTGCTAGCT AG Beta ACT-CTAGCT AG Gamma ACTGCTAGAT AG 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 = dict() for k, v in self.annotations.items(): if k in other.annotations and other.annotations[k] == v: annotations[k] = v column_annotations = dict() 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 ACGGCGTT 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): 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 += 'X' 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_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 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 IndexError('index out of range') 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("ACCGT", "ACG") >>> for alignment in sorted(alignments): ... print("Score = %.1f:" % alignment.score) ... print(alignment) ... Score = 3.0: ACCGT |-||- A-CG- Score = 3.0: ACCGT ||-|- AC-G- Specify the aligner mode as local to generate local alignments: >>> aligner.mode = 'local' >>> alignments = aligner.align("ACCGT", "ACG") >>> for alignment in sorted(alignments): ... print("Score = %.1f:" % alignment.score) ... print(alignment) ... Score = 3.0: ACCGT |-||. A-CG. Score = 3.0: ACCGT ||-|. AC-G. Do a global alignment. Identical characters are given 2 points, 1 point is deducted for each non-identical character. >>> aligner.mode = 'global' >>> aligner.match = 2 >>> aligner.mismatch = -1 >>> for alignment in aligner.align("ACCGT", "ACG"): ... print("Score = %.1f:" % alignment.score) ... print(alignment) ... Score = 6.0: ACCGT ||-|- AC-G- Score = 6.0: ACCGT |-||- A-CG- 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("ACCGT", "ACG"): ... print("Score = %.1f:" % alignment.score) ... print(alignment) ... Score = 5.5: ACCGT |-||- A-CG- Score = 5.5: ACCGT ||-|- AC-G- The alignment function can also use known matrices already included in Biopython: >>> from Bio.SubsMat import MatrixInfo >>> aligner = Align.PairwiseAligner() >>> aligner.substitution_matrix = MatrixInfo.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- """ def align(self, seqA, seqB): seqA = str(seqA) seqB = str(seqB) score, paths = _aligners.PairwiseAligner.align(self, seqA, seqB) alignments = PairwiseAlignments(seqA, seqB, score, paths) return alignments def score(self, seqA, seqB): seqA = str(seqA) seqB = str(seqB) return _aligners.PairwiseAligner.score(self, seqA, seqB) if __name__ == "__main__": from Bio._utils import run_doctest run_doctest()