Python DistanceTreeConstructor.build_tree方法代码示例

# 需要导入模块: from Bio.Phylo.TreeConstruction import DistanceTreeConstructor [as 别名]
# 或者: from Bio.Phylo.TreeConstruction.DistanceTreeConstructor import build_tree [as 别名]
class DistanceTreeConstructorTest(unittest.TestCase):
    """Test DistanceTreeConstructor"""
    def setUp(self):
        self.aln = AlignIO.read(open('TreeConstruction/msa.phy'), 'phylip')
        calculator = DistanceCalculator('blosum62')
        self.dm = calculator.get_distance(self.aln)
        self.constructor = DistanceTreeConstructor(calculator)

    def test_upgma(self):
        tree = self.constructor.upgma(self.dm)
        self.assertTrue(isinstance(tree, BaseTree.Tree))
        tree_file = StringIO.StringIO()
        Phylo.write(tree, tree_file, 'newick')
        ref_tree = open('./TreeConstruction/upgma.tre')
        self.assertEqual(tree_file.getvalue(), ref_tree.readline())
        ref_tree.close()

    def test_nj(self):
        tree = self.constructor.nj(self.dm)
        self.assertTrue(isinstance(tree, BaseTree.Tree))
        tree_file = StringIO.StringIO()
        Phylo.write(tree, tree_file, 'newick')
        ref_tree = open('./TreeConstruction/nj.tre')
        self.assertEqual(tree_file.getvalue(), ref_tree.readline())
        ref_tree.close()

    def test_built_tree(self):
        tree = self.constructor.build_tree(self.aln)
        self.assertTrue(isinstance(tree, BaseTree.Tree))
        tree_file = StringIO.StringIO()
        Phylo.write(tree, tree_file, 'newick')
        ref_tree = open('./TreeConstruction/nj.tre')
        self.assertEqual(tree_file.getvalue(), ref_tree.readline())
        ref_tree.close()

# 需要导入模块: from Bio.Phylo.TreeConstruction import DistanceTreeConstructor [as 别名]
# 或者: from Bio.Phylo.TreeConstruction.DistanceTreeConstructor import build_tree [as 别名]
class DistanceTreeConstructorTest(unittest.TestCase):
    """Test DistanceTreeConstructor"""
    def setUp(self):
        self.aln = AlignIO.read('TreeConstruction/msa.phy', 'phylip')
        calculator = DistanceCalculator('blosum62')
        self.dm = calculator.get_distance(self.aln)
        self.constructor = DistanceTreeConstructor(calculator)

    def test_upgma(self):
        tree = self.constructor.upgma(self.dm)
        self.assertTrue(isinstance(tree, BaseTree.Tree))
        # tree_file = StringIO()
        # Phylo.write(tree, tree_file, 'newick')
        ref_tree = Phylo.read('./TreeConstruction/upgma.tre', 'newick')
        self.assertTrue(Consensus._equal_topology(tree, ref_tree))
        # ref_tree.close()

    def test_nj(self):
        tree = self.constructor.nj(self.dm)
        self.assertTrue(isinstance(tree, BaseTree.Tree))
        # tree_file = StringIO()
        # Phylo.write(tree, tree_file, 'newick')
        ref_tree = Phylo.read('./TreeConstruction/nj.tre', 'newick')
        self.assertTrue(Consensus._equal_topology(tree, ref_tree))
        # ref_tree.close()

    def test_built_tree(self):
        tree = self.constructor.build_tree(self.aln)
        self.assertTrue(isinstance(tree, BaseTree.Tree))
        # tree_file = StringIO()
        # Phylo.write(tree, tree_file, 'newick')
        ref_tree = Phylo.read('./TreeConstruction/nj.tre', 'newick')
        self.assertTrue(Consensus._equal_topology(tree, ref_tree))

# 需要导入模块: from Bio.Phylo.TreeConstruction import DistanceTreeConstructor [as 别名]
# 或者: from Bio.Phylo.TreeConstruction.DistanceTreeConstructor import build_tree [as 别名]
def consensus(msa):
    alignment = MultipleSeqAlignment(msa)
    calculator = DistanceCalculator('identity')
    dm = calculator.get_distance(alignment)
    constructor = DistanceTreeConstructor(calculator, 'nj')
    tree = constructor.build_tree(alignment)
    print tree

# 需要导入模块: from Bio.Phylo.TreeConstruction import DistanceTreeConstructor [as 别名]
# 或者: from Bio.Phylo.TreeConstruction.DistanceTreeConstructor import build_tree [as 别名]
 def tree(self):
     """Returns a phylogenetic tree constructed from the given alignment."""
     calculator = DistanceCalculator(self._distance_model)
     constructor = DistanceTreeConstructor(calculator, self._tree_algorithm)
     tree = constructor.build_tree(self.alignment)
     # Make the tree rooted.
     tree.root_at_midpoint()
     tree.root.name = 'Root'
     return tree

# 需要导入模块: from Bio.Phylo.TreeConstruction import DistanceTreeConstructor [as 别名]
# 或者: from Bio.Phylo.TreeConstruction.DistanceTreeConstructor import build_tree [as 别名]
def dendroNJ(inFile, model='identity', bootstrap=True, replicate=100):
    """
    Given an alingment in fasta format, the function returns a Neighbor Joining tree in newick format.
    Module required:
    - AlignIO (from Bio)
    - DistanceCalculator (from Bio.Phylo.TreeConstruction)
    - DistanceTreeConstructor (from Bio.Phylo.TreeConstruction)
    - bootstrap_consensus (from Bio.Phylo.Consensus)
    Usage: <inFile> <model (default = 'identity')> <bootstrap (default = True)>
                           <replicate (default = 100)>
    """
    aln = AlignIO.read(inFile, 'fasta') # read the alignment
    constructor = DistanceTreeConstructor(DistanceCalculator(model), 'nj')
    if bootstrap:
        tree = bootstrap_consensus(aln, int(replicate), constructor, majority_consensus)
    else:
        tree = constructor.build_tree(aln)
    return tree.format('newick')

# 需要导入模块: from Bio.Phylo.TreeConstruction import DistanceTreeConstructor [as 别名]
# 或者: from Bio.Phylo.TreeConstruction.DistanceTreeConstructor import build_tree [as 别名]
# CAGTTCGCCACAA Gamma

# Several thigns can be done witht he alignment: get a distance matrix from it:
dstcalc = DistanceCalculator('identity')
dm = dstcalc.get_distance(aln)
# DistanceMatrix(names=['Alpha', 'Beta', 'Gamma', 'Delta', 'Epsilon'], matrix=[[0], [0.23076923076923073, 0], [0.3846153846153846, 0.23076923076923073, 0], [0.5384615384615384, 0.5384615384615384, 0.5384615384615384, 0], [0.6153846153846154, 0.3846153846153846, 0.46153846153846156, 0.15384615384615385, 0]])
print "What's the get_distance(aln) from DistanceCalculator('identity') object?"
print type(dm)
print dm
# Alpha   0
# Beta    0.230769230769  0
# Gamma   0.384615384615  0.230769230769  0
# Delta   0.538461538462  0.538461538462  0.538461538462  0
# Epsilon 0.615384615385  0.384615384615  0.461538461538  0.153846153846  0

# build a tree from it.
from Bio.Phylo.TreeConstruction import DistanceTreeConstructor

construc0 = DistanceTreeConstructor(dstcalc, 'nj')
tre0 = construc0.build_tree(aln)
print type(tre0)
# as you can see from abovedstcalc is needed for te constructor and then
# to build the tree the alignment is needed. That's two things which need to originae fromt he same thing.
# A bit of a tall order
# You can build the tree from a distance matrix only, by leaving out the aln argument
# by not using the build_tree method on the constructor, but rather the .nj method

construc2 = DistanceTreeConstructor()
tre2 = construc2.nj(dm)
print type(tre2)