### Navigation

- index
- modules |
- modules |
- Pydna 0.6.0 documentation »
- Module code »

# Source code for pydna.assembly

    #!/usr/bin/env python
    # -*- coding: utf-8 -*-
    '''This module provides functions for assembly of sequences by homologous recombination and other
    related techniques. Given a list of sequences (Dseqrecords), all sequences will be analyzed for
    overlapping regions of DNA (common substrings).

    The assembly algorithm is based on graph theory where each overlapping region forms a node and
    sequences separating the overlapping regions form edges.

    '''

    import itertools
    import networkx as nx
    import operator
    import random

    from copy import copy
    from textwrap import dedent
    from collections import defaultdict
    from collections import namedtuple

    from Bio.SeqFeature import ExactPosition
    from Bio.SeqFeature import FeatureLocation
    from Bio.SeqFeature import SeqFeature

    from pydna.dsdna import Dseq
    from pydna.dsdna import Dseqrecord
    from pydna._simple_paths8 import all_simple_paths_edges, all_circular_paths_edges
    from findsubstrings_suffix_arrays_python import common_sub_strings
    from findsubstrings_suffix_arrays_python import terminal_overlap

    from orderedset import OrderedSet

    class Fragment(Dseqrecord):
        '''This class holds information about a DNA fragment in an assembly.
        This class is instantiated by the :class:`Assembly` class and is not
        meant to be instantiated directly.

        '''

        def __init__(self, record, start1    = 0,
                                   end1      = 0,
                                   start2    = 0,
                                   end2      = 0,
                                   alignment = 0,
                                   i         = 0, *args, **kwargs):

            super(Fragment, self).__init__(record, *args, **kwargs)

            self.start1             = start1
            self.end1               = end1
            self.left_overlap_size  = end1-start1
            self.start2             = start2
            self.end2               = end2
            self.right_overlap_size = end2-start2
            self.alignment          = alignment
            self.i                  = i

        def __str__(self):
            return ("Fragment alignment {}\n").format(self.alignment)+super(Fragment, self).__str__()

    class Contig(Dseqrecord):
        '''This class holds information about a DNA assembly. This class is instantiated by
        the :class:`Assembly` class and is not meant to be instantiated directly.

        '''

        def __init__(self,
                     record,
                     source_fragments=[],
                     *args, **kwargs):

            super(Contig, self).__init__(record, *args, **kwargs)
            self.source_fragments = source_fragments
            self.number_of_fragments = len(self.source_fragments)

        def detailed_figure(self):
            '''Synonym of :func:`detailed_fig`'''
            return self.detailed_fig()

        def detailed_fig(self):

            fig=""
            for s in self.source_fragments:
                fig +="{}{}\n".format(" "*s.alignment, s.seq.tostring())
            return fig

        def small_figure(self):
            '''Synonym of :func:`small_fig`'''
            return self.small_fig()

        def small_fig(self):
            '''
            Returns a small ascii representation of the assembled fragments. Each fragment is
            represented by:

            ::

             Size of common 5' substring|Name and size of DNA fragment| Size of common 5' substring

            Linear:

            ::

              frag20| 6
                     \\/
                     /\\
                      6|frag23| 6
                               \\/
                               /\\
                                6|frag14

            Circular:

            ::

              -|2577|61
             |       \\/
             |       /\\
             |       61|5681|98
             |               \\/
             |               /\\
             |               98|2389|557
             |                       \\/
             |                       /\\
             |                       557-
             |                          |
              --------------------------

            '''

            if self.linear:
                '''
                frag20| 6
                       \/
                       /\
                        6|frag23| 6
                                 \/
                                 /\
                                  6|frag14
                '''
                f = self.source_fragments[0]
                space2 = len(f.name)

                fig = ("{name}|{o2:>2}\n"
                       "{space2} \/\n"
                       "{space2} /\\\n").format(name = f.name,
                                                o2 = f.right_overlap_size,
                                                space2 = " "*space2)
                space = len(f.name)

                for f in self.source_fragments[1:-1]:
                    name= "{o1:>2}|{name}|".format(o1   = f.left_overlap_size,
                                                   name = f.name)
                    space2 = len(name)
                    fig +=("{space} {name}{o2:>2}\n"
                           "{space} {space2}\/\n"
                           "{space} {space2}/\\\n").format( name = name,
                                                            o2 = f.right_overlap_size,
                                                            space = " "*space,
                                                            space2 = " "*space2)
                    space +=space2
                f = self.source_fragments[-1]
                fig += ("{space} {o1:>2}|{name}").format(name = f.name,
                                                        o1 = f.left_overlap_size,
                                                        space = " "*(space))

            else:
                '''
                 -|2577|61
                |       \/
                |       /\
                |       61|5681|98
                |               \/
                |               /\
                |               98|2389|557
                |                       \/
                |                       /\
                |                       557-
                |                          |
                 --------------------------
                '''
                f = self.source_fragments[0]
                space = len(f.name)+3
                fig =(" -|{name}|{o2:>2}\n"
                      "|{space}\/\n"
                      "|{space}/\\\n").format(name = f.name,
                                               o2 = f.right_overlap_size,
                                               space = " "*space)
                for f in self.source_fragments[1:]:
                    name= "{o1:>2}|{name}|".format(o1 = f.left_overlap_size,
                                                          name = f.name)
                    space2 = len(name)
                    fig +=("|{space}{name}{o2:>2}\n"
                           "|{space}{space2}\/\n"
                           "|{space}{space2}/\\\n").format(o2 = f.right_overlap_size,
                                                           name = name,
                                                           space = " "*space,
                                                           space2 = " "*space2)
                    space +=space2

                fig +="|{space}{o1:>2}-\n".format(space=" "*(space), o1=self.source_fragments[0].left_overlap_size)
                fig +="|{space}   |\n".format(space=" "*(space))
                fig +=" {space}".format(space="-"*(space+3))
            return dedent(fig)

    class Assembly(object):
        '''Assembly of a list of linear DNA fragments into linear or circular constructs.
        Accepts a list of Dseqrecords (source fragments) to initiate an Assembly object.
        Several methods are available for analysis of overlapping sequences, graph construction
        and assembly.

        Parameters
        ----------

        dsrecs : list
            a list of Dseqrecord objects.

        Examples
        --------

        >>> from pydna import Assembly, Dseqrecord
        >>> a = Dseqrecord("acgatgctatactgCCCCCtgtgctgtgctcta")
        >>> b = Dseqrecord("tgtgctgtgctctaTTTTTtattctggctgtatc")
        >>> c = Dseqrecord("tattctggctgtatcGGGGGtacgatgctatactg")
        >>> x = Assembly((a,b,c), limit=14)
        >>> x.analyze_overlaps()
        '6 sequences analyzed of which 3 have shared homologies with totally 3 overlaps'
        >>> x.create_graph()
        "A graph with 5', 3' and 3 internal nodes was created"
        >>> x.assemble_circular_from_graph()
        '1 circular products were formed'
        >>> x
        Assembly object:
        Sequences........................: 33, 34, 35
        Sequences with shared homologies.: 33, 34, 35
        Homology limit (bp)..............: 14
        Number of overlaps...............: 3
        Nodes in graph...................: 5
        Assembly protocol................: overlaps
        Circular products................: 59
        Linear products..................: No linear products
        >>> x.circular_products
        [Dseqrecord(o59)]
        >>> x.circular_products[0].seq.watson
        'CCCCCtgtgctgtgctctaTTTTTtattctggctgtatcGGGGGtacgatgctatactg'

        '''

        def __init__(self, dsrecs, limit = 25):
            self.dsrecs    = dsrecs
            ''' Sequences fed to this class is stored in this property'''
            self.max_nodes = len(self.dsrecs)
            ''' The max number of nodes allowed. This can be reset to some other value'''
            self.limit     = limit
            ''' The shortest common sub strings to be considered '''

            for dr in self.dsrecs:
                if dr.name in ("",".", "<unknown name>", None):
                    dr.name = "frag{}".format(len(dr))

        def analyze_overlaps(self, limit=None):
            '''This method carries out a pairwise analysis for common sub strings (shared homologous sequences)
            among DNA fragments stored in the dsrecs property.

            * Common sub strings need to be equal to or longer than limit.
            * Common sub strings can be present anywhere within the sequences stored in the dsrecs property.

            The analyzed_dsrec property will contain copies of the sequences in the dsrecs property that have
            common substrings. Common sub strings are added as features to the sequences in the analyzed_dsrec
            property.

            Parameters
            ----------

            limit : int
                The shortest shared sub sequence to be considered. This will also set the limit property.

            See also
            --------
            pydna.assembly.Assembly.analyze_terminal_overlaps

            '''

            if limit:
                self.limit = limit
            self.protocol = "overlaps"
            return self._analyze_overlaps(common_sub_strings)

        def analyze_terminal_overlaps(self, limit=None):
            '''This method carries out a pairwise analysis for shared sub sequences equal to or longer than
            limit. The difference between this method and :func:`analyze_overlaps` is that shared sequences
            must start or end at the extremities of the source fragments.

            Parameters
            ----------

            limit : int
                The shortest shared sub sequence to be considered. This will also set the limit property.

            See also
            --------
            pydna.assembly.Assembly.analyze_overlaps

            '''
            if limit:
                self.limit = limit
            self.protocol = "terminal overlaps"
            return self._analyze_overlaps(terminal_overlap)

        def create_graph(self):
            '''Creates a graph from analyzed source fragments. Nodes in the graph are shared sub sequences
            found as features in the source sequences. Edges are the sequences that connect the shared
            sub sequences in each source fragment. Two additional nodes called 5' and 3' are also added to
            represent DNA ends.
            '''
            return self._create_graph()

        def assemble_circular_from_graph(self):
            '''Assembles all circular products from the graph created by :func:`create_graph`'''
            self.circular_products = self._circ()
            return "{} circular products were formed".format(len(self.circular_products))

        def assemble_linear_from_graph(self):
            '''Assembles all linear products from the graph created by :func:`create_graph`'''
            self.linear_products = self._lin()
            return "{} linear products were formed".format(len(self.linear_products))

        def assemble_hr_circular(self, limit=None):
            '''Convenience method to assembles all possible circular homologous recombination (hr) products
            expected from in-vivo homologous recombination by the following steps:

            1. Analysis of source fragments using the :func:`analyze_overlaps` method
            2. Construction of a graph using the :func:`create_graph` method
            3. Assembly of possible circular products using the :func:`assemble_circular_from_graph` method

            The property "circular_products" is initiated with a list of :class:`Fragment` objects.

            '''
            if limit:
                self.limit = limit
            self.analyze_overlaps()
            self.create_graph()
            self.assemble_circular_from_graph()
            self.protocol = "homologous recombination, circular"
            return "{} circular products were formed".format(len(self.circular_products))

        def assemble_hr_linear(self, limit = None):
            '''Convenience method to assembles all possible linear homologous recombination (hr) products
            expected from in-vivo homologous recombination by the following steps:

            1. Analysis of source fragments using the :func:`analyze_overlaps` method
            2. Construction of a graph using the :func:`create_graph` method
            3. Assembly of possible linear products using the :func:`assemble_linear_from_graph` method

            The property "linear_products" is initiated with a list of :class:`Fragment` objects.

            '''
            if limit:
                self.limit = limit
            self.analyze_overlaps()
            self._create_graph()
            self.linear_products = self._lin()
            self.protocol = "homologous recombination, linear"
            return "{} linear products were formed".format(len(self.linear_products))

        def assemble_gibson_circular(self, limit = None):
            '''Convenience method to assembles all possible circular Gibson assembly products
            expected from in-vivo homologous recombination by the following steps:

            1. Analysis of source fragments using the :func:`analyze_terminal_overlaps` method
            2. Construction of a graph using the :func:`create_graph` method
            3. Assembly of possible circular products using the :func:`assemble_circular_from_graph` method

            The property "circular_products" is initiated with a list of :class:`Fragment` objects.

            '''
            if limit:
                self.limit = limit
            self.analyze_terminal_overlaps()
            self._create_graph()
            self.circular_products = self._circ()
            self.protocol = "gibson assembly, circular"
            return "{} circular products were formed with the following sizes (bp): {}".format(len(self.circular_products),
                                                                                               ", ".join(str(len(x)) for x in self.circular_products))

        def assemble_gibson_linear(self, limit = None):
            '''Convenience method to assembles all possible linear Gibson assembly products
            expected from in-vivo homologous recombination by the following steps:

            1. Analysis of source fragments using the :func:`analyze_terminal_overlaps` method
            2. Construction of a graph using the :func:`create_graph` method
            3. Assembly of possible circular products using the :func:`assemble_linear_from_graph` method

            The property "linear_products" is initiated with a list of :class:`Fragment` objects.

            '''
            if limit:
                self.limit = limit
            self.analyze_terminal_overlaps()
            self._create_graph()
            self.linear_products = self._lin()
            self.protocol = "gibson assembly, linear"
            return "{} linear products were formed with the following sizes (bp): {}".format( len(self.linear_products),
                                                                                              ", ".join(str(len(x)) for x in self.linear_products))
        def assemble_fusion_pcr_linear(self, limit = None):
            '''Convenience method to assembles all possible linear fusion PCR products.
            This method is a synonym of :func:`assemble_gibson_linear`
            '''
            self.assemble_gibson_linear(limit)
            self.protocol = "fusion PCR, linear"
            return "{} linear products were formed".format(len(self.linear_products))

        def assemble_slic(self, limit = None):
            '''Not implemented'''
            self.protocol = "slic, linear"
            raise NotImplementedError

        def assemble_golden_gate(self, limit = None):
            '''Not implemented'''
            self.protocol = "golden_gate"
            raise NotImplementedError

        def _create_graph(self):

            self.G=nx.MultiDiGraph(multiedges=True, name ="original graph" , selfloops=False)
            self.G.add_node( '5' )
            self.G.add_node( '3' )

            for i, dsrec in enumerate(self.analyzed_dsrecs):

                overlaps = sorted( {f.qualifiers['chksum'][0]:f for f in dsrec.features
                                    if f.type=='overlap'}.values(),
                                   key = operator.attrgetter('location.start'))

                if overlaps:
                    overlaps = ([SeqFeature(FeatureLocation(0, 0),
                                 type = 'overlap',
                                 qualifiers = {'chksum':['5']})]+
                                 overlaps+
                                [SeqFeature(FeatureLocation(len(dsrec),len(dsrec)),
                                            type = 'overlap',
                                            qualifiers = {'chksum':['3']})])

                    for olp1, olp2 in itertools.combinations(overlaps, 2):

                        n1 = olp1.qualifiers['chksum'][0]
                        n2 = olp2.qualifiers['chksum'][0]

                        if n1 == '5' and n2=='3':
                            continue

                        s1,e1,s2,e2 = (olp1.location.start.position,
                                       olp1.location.end.position,
                                       olp2.location.start.position,
                                       olp2.location.end.position,)

                        source_fragment = Fragment(dsrec,s1,e1,s2,e2,i)

                        self.G.add_edge( n1, n2,
                                         frag=source_fragment,
                                         weight = s1-e1,
                                         i = i)
            return '''A graph with 5', 3' and {nodes} internal nodes was created'''.format(nodes = self.G.order()-2)

        def _analyze_overlaps(self, algorithm):
            cols = {}
            for dsrec in self.dsrecs:
                dsrec.features = [f for f in dsrec.features if f.type!="overlap"]
                dsrec.seq = Dseq(dsrec.seq.todata)
            rcs = {dsrec:dsrec.rc() for dsrec in self.dsrecs}
            matches=[]
            dsset=OrderedSet()

            for a, b in itertools.combinations(self.dsrecs, 2):
                #print len(a),len(b)
                #a,b = b,a
                match = algorithm( str(a.seq).upper(),
                                   str(b.seq).upper(),
                                   self.limit)
                if match:
                    matches.append((a, b, match))
                    dsset.add(a)
                    dsset.add(b)
                match = algorithm( str(a.seq).upper(),
                                   str(rcs[b].seq).upper(),
                                   self.limit)
                if match:
                    matches.append((a, rcs[b], match))
                    dsset.add(a)
                    dsset.add(rcs[b])
                    matches.append((rcs[a], b, [(len(a)-sa-le,len(b)-sb-le,le) for sa,sb,le in match]))
                    dsset.add(b)
                    dsset.add(rcs[a])

            self.no_of_olaps=0

            for a, b, match in matches:
                for start_in_a, start_in_b, length in match:
                    self.no_of_olaps+=1
                    chksum = a[start_in_a:start_in_a+length].seguid()
                    assert chksum == b[start_in_b:start_in_b+length].seguid()

                    try:
                        fcol, revcol = cols[chksum]
                    except KeyError:
                        fcol = '#%02X%02X%02X' % (random.randint(175,255),random.randint(175,255),random.randint(175,255))
                        rcol = '#%02X%02X%02X' % (random.randint(175,255),random.randint(175,255),random.randint(175,255))
                        cols[chksum] = fcol,rcol

                    qual      = {"note"             : ["olp_{}".format(chksum)],
                                 "chksum"           : [chksum],
                                 "ApEinfo_fwdcolor" : [fcol],
                                 "ApEinfo_revcolor" : [rcol]}

                    if not chksum in [f.qualifiers["chksum"][0] for f in a.features if f.type == "overlap"]:
                        a.features.append( SeqFeature( FeatureLocation(start_in_a,
                                                                       start_in_a + length),
                                                                       type = "overlap",
                                                                       qualifiers = qual))
                    if not chksum in [f.qualifiers["chksum"][0] for f in b.features if f.type == "overlap"]:
                        b.features.append( SeqFeature( FeatureLocation(start_in_b,
                                                                       start_in_b + length),
                                                                       type = "overlap",
                                                                       qualifiers = qual))
            for ds in dsset:
                ds.features = sorted([f for f in ds.features], key = operator.attrgetter("location.start"))

            self.analyzed_dsrecs = list(dsset)

            return ( "{number_of_seqs} sequences analyzed "
                     "of which {analyzed_dsrecs} have shared homologies "
                     "with totally {no_of_olaps} overlaps").format(number_of_seqs  = len(self.dsrecs)*2,
                                                                   analyzed_dsrecs = len(self.analyzed_dsrecs),
                                                                   no_of_olaps     = self.no_of_olaps)

        def _circ(self):
            self.cG = self.G.copy()
            self.cG.remove_nodes_from(('5','3'))
            circular_products=defaultdict(list)

            for pth in all_circular_paths_edges(self.cG):

                ns = min(enumerate(pth), key = lambda x:x[1][2]['i'])[0]

                path = pth[ns:]+pth[:ns]

                pred_frag = copy(path[0][2]['frag'])

                source_fragments = [pred_frag, ]

                if pred_frag.start2<pred_frag.end1:
                    result=pred_frag[pred_frag.start2+(pred_frag.end1-pred_frag.start2):pred_frag.end2]
                else:
                    result=pred_frag[pred_frag.end1:pred_frag.end2]

                result.seq = Dseq(result.seq.tostring())

                for first_node, second_node, edgedict in path[1:]:

                    f  = copy(edgedict['frag'])

                    f.alignment =  pred_frag.alignment + pred_frag.start2- f.start1
                    source_fragments.append(f)

                    if f.start2>f.end1:
                        nxt = f[f.end1:f.end2]
                    else:
                        nxt =f[f.start2+(f.end1-f.start2):f.end2]
                    nxt.seq = Dseq(nxt.seq.tostring())
                    result+=nxt

                    pred_frag = f

                add=True
                for cp in circular_products[len(result)]:
                    if (str(result.seq).lower() in str(cp.seq).lower()*2
                        or
                        str(result.seq).lower() == str(cp.seq.reverse_complement()).lower()*2):
                        pass
                        add=False
                if add:
                    circular_products[len(result)].append( Contig( Dseqrecord(result, circular=True), source_fragments))

            return list(itertools.chain.from_iterable(circular_products[size] for size in sorted(circular_products, reverse=True)))

        def _lin(self):

            linear_products=defaultdict(list)

            for path in all_simple_paths_edges(self.G, '5', '3', data=True, cutoff=self.max_nodes):

                pred_frag = copy(path[0][2].values().pop()['frag'])
                source_fragments = [pred_frag, ]

                if pred_frag.start2<pred_frag.end1:
                    result=pred_frag[pred_frag.start2+(pred_frag.end1-pred_frag.start2):pred_frag.end2]
                else:
                    result=pred_frag[pred_frag.end1:pred_frag.end2]

                for first_node, second_node, edgedict in path[1:]:

                    edgedict = edgedict.values().pop()

                    f  = copy(edgedict['frag'])

                    f.alignment =  pred_frag.alignment + pred_frag.start2- f.start1
                    source_fragments.append(f)

                    if f.start2>f.end1:
                        result+=f[f.end1:f.end2]
                    else:
                        result+=f[f.start2+(f.end1-f.start2):f.end2]

                    pred_frag = f

                add=True
                for lp in linear_products[len(result)]:
                    if (str(result.seq).lower() == str(lp.seq).lower()
                        or
                        str(result.seq).lower() == str(lp.seq.reverse_complement()).lower()):
                        add=False
                for dsrec in self.dsrecs:
                    if (str(result.seq).lower() == str(dsrec.seq).lower()
                        or
                        str(result.seq).lower() == str(dsrec.seq.reverse_complement()).lower()):
                        add=False
                if add:
                    linear_products[len(result)].append(Contig( result, source_fragments))

            return list(itertools.chain.from_iterable(linear_products[size] for size in sorted(linear_products, reverse=True)))

        def __repr__(self):

            try:
                number_of_seqs  =  ", ".join(str(len(x)) for x in self.dsrecs)
            except AttributeError:
                number_of_seqs  =  "No sequences"
            try:
                analyzed_dsrecs = ", ".join(str(len(x)) for x in self.analyzed_dsrecs)
            except AttributeError:
                analyzed_dsrecs = "No analyzed sequences"
            try:
                limit = self.limit
            except AttributeError:
                limit = "No limit set"
            try:
                no_of_olaps = self.no_of_olaps
            except AttributeError:
                no_of_olaps = "No overlaps"
            try:
                nodes = self.G.order()
            except AttributeError:
                nodes = "No graph"
            try:
                pr = self.protocol
            except AttributeError:
                pr= "No protocol"
            try:
                cp = ", ".join(str(len(x)) for x in self.circular_products)
            except AttributeError:
                cp= "No circular products"
            try:
                lp = ", ".join(str(len(x)) for x in self.linear_products)
            except AttributeError:
                lp= "No linear products"

            return   ( "Assembly object:\n"
                       "Sequences........................: {number_of_seqs}\n"
                       "Sequences with shared homologies.: {analyzed_dsrecs}\n"
                       "Homology limit (bp)..............: {limit}\n"
                       "Number of overlaps...............: {no_of_olaps}\n"
                       "Nodes in graph...................: {nodes}\n"
                       "Assembly protocol................: {pr}\n"
                       "Circular products................: {cp}\n"
                       "Linear products..................: {lp}"    ).format(number_of_seqs  = number_of_seqs,
                                                                             analyzed_dsrecs = analyzed_dsrecs,
                                                                             limit           = limit,
                                                                             no_of_olaps     = no_of_olaps,
                                                                             nodes           = nodes,
                                                                             pr              = pr,
                                                                             cp              = cp,
                                                                             lp              = lp)

    if __name__=="__main__":
        import doctest
        doctest.testmod()

        from pydna_helper import ape
        from pydna import Dseqrecord, Dseq
        from pydna import parse
        from pydna import eq
        from pprint import pprint

        a = Dseqrecord(Dseq("acgatgctatactgCCCCCtgtgctgtgctcta",
                            "tgctacgatatgacGGGGGacacgacacgagat"[::-1]))

        b = Dseqrecord(Dseq("tgtgctgtgctctaTTTTTtattctggctgtatc",
                            "acacgacacgagatAAAAAataagaccgacatag"[::-1]))

        c = Dseqrecord(Dseq("tattctggctgtatcGGGGGtacgatgctatactg",
                            "ataagaccgacatagCCCCCatgctacgatatgac"[::-1]))

        pw = [a,c,b]

        a = Assembly(pw, limit=14)

        print a.assemble_hr_circular()

        print a.circular_products

        #print a.circular_products[0].small_fig()

        #print a.circular_products[0].seq

        #print '''CCCCCtgtgctgtgctctaTTTTTtattctggctgtatcGGGGGtacgatgctatactg'''

        #for x in a.circular_products:
            #print x.seq
        #    print x.source_fragments
        #    print

### Navigation

- index
- modules |
- modules |
- Pydna 0.6.0 documentation »
- Module code »