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# Copyright (C) 2013 by Yanbo Ye (yeyanbo289@gmail.com)
# This code is part of the Biopython distribution and governed by its
# license. Please see the LICENSE file that should have been included
# as part of this package.
"""Unit tests for the Bio.Phylo.TreeConstruction module."""
import os
import tempfile
import unittest
from io import StringIO
from itertools import combinations
from Bio import Align
from Bio import AlignIO
from Bio import Phylo
from Bio.Phylo import BaseTree
from Bio.Phylo import Consensus
from Bio.Phylo import TreeConstruction
from Bio.Phylo.TreeConstruction import _Matrix
from Bio.Phylo.TreeConstruction import DistanceCalculator
from Bio.Phylo.TreeConstruction import DistanceMatrix
from Bio.Phylo.TreeConstruction import DistanceTreeConstructor
from Bio.Phylo.TreeConstruction import NNITreeSearcher
from Bio.Phylo.TreeConstruction import ParsimonyScorer
from Bio.Phylo.TreeConstruction import ParsimonyTreeConstructor
temp_dir = tempfile.mkdtemp()
class DistanceMatrixTest(unittest.TestCase):
"""Test for DistanceMatrix construction and manipulation."""
def setUp(self):
self.names = ["Alpha", "Beta", "Gamma", "Delta"]
self.matrix = [[0], [1, 0], [2, 3, 0], [4, 5, 6, 0]]
def test_good_construction(self):
dm = DistanceMatrix(self.names, self.matrix)
self.assertIsInstance(dm, TreeConstruction.DistanceMatrix)
self.assertEqual(dm.names[0], "Alpha")
self.assertEqual(dm.matrix[2][1], 3)
self.assertEqual(len(dm), 4)
self.assertEqual(
repr(dm),
"DistanceMatrix(names=['Alpha', 'Beta', 'Gamma', 'Delta'], "
"matrix=[[0], [1, 0], [2, 3, 0], [4, 5, 6, 0]])",
)
def test_bad_construction(self):
self.assertRaises(
TypeError,
DistanceMatrix,
["Alpha", 100, "Gamma", "Delta"],
[[0], [0.1, 0], [0.2, 0.3, 0], [0.4, 0.5, 0.6, 0]],
)
self.assertRaises(
TypeError,
DistanceMatrix,
["Alpha", "Beta", "Gamma", "Delta"],
[[0], ["a"], [0.2, 0.3], [0.4, 0.5, 0.6]],
)
self.assertRaises(
ValueError,
DistanceMatrix,
["Alpha", "Alpha", "Gamma", "Delta"],
[[0], [0.1], [0.2, 0.3], [0.4, 0.5, 0.6]],
)
self.assertRaises(
ValueError,
DistanceMatrix,
["Alpha", "Beta", "Gamma", "Delta"],
[[0], [0.2, 0], [0.4, 0.5, 0.6]],
)
self.assertRaises(
ValueError,
DistanceMatrix,
["Alpha", "Beta", "Gamma", "Delta"],
[[0], [0.1], [0.2, 0.3, 0.4], [0.4, 0.5, 0.6]],
)
def test_good_manipulation(self):
dm = DistanceMatrix(self.names, self.matrix)
# getitem
self.assertEqual(dm[1], [1, 0, 3, 5])
self.assertEqual(dm[2, 1], 3)
self.assertEqual(dm[2][1], 3)
self.assertEqual(dm[1, 2], 3)
self.assertEqual(dm[1][2], 3)
self.assertEqual(dm["Alpha"], [0, 1, 2, 4])
self.assertEqual(dm["Gamma", "Delta"], 6)
# setitem
dm["Alpha"] = [0, 10, 20, 40]
self.assertEqual(dm["Alpha"], [0, 10, 20, 40])
# delitem insert item
del dm[1]
self.assertEqual(dm.names, ["Alpha", "Gamma", "Delta"])
self.assertEqual(dm.matrix, [[0], [20, 0], [40, 6, 0]])
dm.insert("Beta", [1, 0, 3, 5], 1)
self.assertEqual(dm.names, self.names)
self.assertEqual(dm.matrix, [[0], [1, 0], [20, 3, 0], [40, 5, 6, 0]])
del dm["Alpha"]
self.assertEqual(dm.names, ["Beta", "Gamma", "Delta"])
self.assertEqual(dm.matrix, [[0], [3, 0], [5, 6, 0]])
dm.insert("Alpha", [1, 2, 4, 0])
self.assertEqual(dm.names, ["Beta", "Gamma", "Delta", "Alpha"])
self.assertEqual(dm.matrix, [[0], [3, 0], [5, 6, 0], [1, 2, 4, 0]])
def test_bad_manipulation(self):
dm = DistanceMatrix(self.names, self.matrix)
# getitem
self.assertRaises(ValueError, dm.__getitem__, "A")
self.assertRaises(ValueError, dm.__getitem__, ("Alpha", "A"))
self.assertRaises(TypeError, dm.__getitem__, (1, "A"))
self.assertRaises(TypeError, dm.__getitem__, (1, 1.2))
self.assertRaises(IndexError, dm.__getitem__, 6)
self.assertRaises(IndexError, dm.__getitem__, (10, 10))
# setitem: item or index test
self.assertRaises(ValueError, dm.__setitem__, "A", [1, 3, 4])
self.assertRaises(ValueError, dm.__setitem__, ("Alpha", "A"), 4)
self.assertRaises(TypeError, dm.__setitem__, (1, "A"), 3)
self.assertRaises(TypeError, dm.__setitem__, (1, 1.2), 2)
self.assertRaises(IndexError, dm.__setitem__, 6, [1, 3, 4])
self.assertRaises(IndexError, dm.__setitem__, (10, 10), 1)
# setitem: value test
self.assertRaises(ValueError, dm.__setitem__, 0, [1, 2])
self.assertRaises(TypeError, dm.__setitem__, ("Alpha", "Beta"), "a")
self.assertRaises(TypeError, dm.__setitem__, "Alpha", ["a", "b", "c"])
def test_format_phylip(self):
dm = DistanceMatrix(self.names, self.matrix)
handle = StringIO()
dm.format_phylip(handle)
lines = handle.getvalue().splitlines()
self.assertEqual(len(lines), len(dm) + 1)
self.assertTrue(lines[0].endswith(str(len(dm))))
for name, line in zip(self.names, lines[1:]):
self.assertTrue(line.startswith(name))
class DistanceCalculatorTest(unittest.TestCase):
"""Test DistanceCalculator."""
def test_known_matrices_msa(self):
msa = AlignIO.read("TreeConstruction/msa.phy", "phylip")
calculator = DistanceCalculator("identity")
dm = calculator.get_distance(msa)
self.assertEqual(dm["Alpha", "Beta"], 1 - 10 / 13)
calculator = DistanceCalculator("blastn")
dm = calculator.get_distance(msa)
self.assertEqual(dm["Alpha", "Beta"], 1 - 38 / 65)
calculator = DistanceCalculator("trans")
dm = calculator.get_distance(msa)
self.assertEqual(dm["Alpha", "Beta"], 1 - 54 / 65)
calculator = DistanceCalculator("blosum62")
dm = calculator.get_distance(msa)
self.assertEqual(dm["Alpha", "Beta"], 1 - 53 / 84)
def test_known_matrices(self):
aln = Align.read("TreeConstruction/msa.phy", "phylip")
calculator = DistanceCalculator("identity")
dm = calculator.get_distance(aln)
self.assertEqual(dm["Alpha", "Beta"], 1 - 10 / 13)
calculator = DistanceCalculator("blastn")
dm = calculator.get_distance(aln)
self.assertEqual(dm["Alpha", "Beta"], 1 - 38 / 65)
calculator = DistanceCalculator("trans")
dm = calculator.get_distance(aln)
self.assertEqual(dm["Alpha", "Beta"], 1 - 54 / 65)
calculator = DistanceCalculator("blosum62")
dm = calculator.get_distance(aln)
self.assertEqual(dm["Alpha", "Beta"], 1 - 53 / 84)
def test_nonmatching_seqs_msa(self):
aln = AlignIO.read(StringIO(">Alpha\nA-A--\n>Gamma\n-Y-Y-"), "fasta")
# With a proper scoring matrix -- no matches
dmat = DistanceCalculator("blosum62").get_distance(aln)
self.assertEqual(dmat["Alpha", "Alpha"], 0.0)
self.assertEqual(dmat["Alpha", "Gamma"], 1.0)
# Comparing characters only -- 4 misses, 1 match
dmat = DistanceCalculator().get_distance(aln)
self.assertEqual(dmat["Alpha", "Alpha"], 0.0)
self.assertAlmostEqual(dmat["Alpha", "Gamma"], 4.0 / 5.0)
def test_nonmatching_seqs(self):
aln = Align.read(
StringIO(">Alpha\nA-A--\n>Beta\nXXXXX\n>Gamma\n-Y-Y-"), "fasta"
)
# With a proper scoring matrix -- no matches
dmat = DistanceCalculator("blosum62").get_distance(aln)
self.assertEqual(dmat["Alpha", "Alpha"], 0.0)
self.assertEqual(dmat["Alpha", "Gamma"], 1.0)
# Comparing characters only -- 4 misses, 1 match
dmat = DistanceCalculator().get_distance(aln)
self.assertEqual(dmat["Alpha", "Alpha"], 0.0)
self.assertAlmostEqual(dmat["Alpha", "Gamma"], 4.0 / 5.0)
class DistanceTreeConstructorTest(unittest.TestCase):
"""Test DistanceTreeConstructor."""
def setUp(self):
self.msa = AlignIO.read("TreeConstruction/msa.phy", "phylip")
calculator = DistanceCalculator("blosum62")
self.dm_msa = calculator.get_distance(self.msa)
self.constructor_msa = DistanceTreeConstructor(calculator)
self.alignment = Align.read("TreeConstruction/msa.phy", "phylip")
calculator = DistanceCalculator("blosum62")
self.dm = calculator.get_distance(self.alignment)
self.constructor = DistanceTreeConstructor(calculator)
def test_upgma_msa(self):
tree = self.constructor.upgma(self.dm_msa)
self.assertIsInstance(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_upgma(self):
tree = self.constructor.upgma(self.dm)
self.assertIsInstance(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))
# check for equal distance of all terminal nodes from the root
ref_tree.root_at_midpoint()
for len1, len2 in combinations(
[depth for node, depth in ref_tree.depths().items() if node.is_terminal()],
2,
):
self.assertAlmostEqual(len1, len2)
def test_nj_msa(self):
tree = self.constructor.nj(self.dm_msa)
self.assertIsInstance(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()
# create a matrix of length 2
calculator = DistanceCalculator("blosum62")
self.min_dm = calculator.get_distance(self.msa)
for i in range(len(self.min_dm) - 2):
del self.min_dm[len(self.min_dm) - 1]
min_tree = self.constructor.nj(self.min_dm)
self.assertIsInstance(min_tree, BaseTree.Tree)
ref_min_tree = Phylo.read("./TreeConstruction/nj_min.tre", "newick")
self.assertTrue(Consensus._equal_topology(min_tree, ref_min_tree))
def test_nj(self):
tree = self.constructor.nj(self.dm)
self.assertIsInstance(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()
# create a matrix of length 2
calculator = DistanceCalculator("blosum62")
self.min_dm = calculator.get_distance(self.msa)
for i in range(len(self.min_dm) - 2):
del self.min_dm[len(self.min_dm) - 1]
min_tree = self.constructor.nj(self.min_dm)
self.assertIsInstance(min_tree, BaseTree.Tree)
ref_min_tree = Phylo.read("./TreeConstruction/nj_min.tre", "newick")
self.assertTrue(Consensus._equal_topology(min_tree, ref_min_tree))
def test_built_tree_msa(self):
tree = self.constructor.build_tree(self.msa)
self.assertIsInstance(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.alignment)
self.assertIsInstance(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()
class ParsimonyScorerTest(unittest.TestCase):
"""Test ParsimonyScorer."""
def test_get_score_msa(self):
aln = AlignIO.read("TreeConstruction/msa.phy", "phylip")
tree = Phylo.read("./TreeConstruction/upgma.tre", "newick")
scorer = ParsimonyScorer()
score = scorer.get_score(tree, aln)
self.assertEqual(score, 2 + 1 + 2 + 2 + 1 + 1 + 1 + 3)
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3.5 + 2.5 + 3.5 + 3.5 + 2.5 + 1 + 2.5 + 4.5)
alphabet = [
"A",
"C",
"D",
"E",
"F",
"G",
"H",
"I",
"K",
"L",
"M",
"N",
"P",
"Q",
"R",
"1",
"2",
"T",
"V",
"W",
"Y",
"*",
"-",
]
step_matrix = [
[0],
[2, 0],
[1, 2, 0],
[1, 2, 1, 0],
[2, 1, 2, 2, 0],
[1, 1, 1, 1, 2, 0],
[2, 2, 1, 2, 2, 2, 0],
[2, 2, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 2, 1, 0],
[2, 2, 2, 2, 1, 2, 1, 1, 2, 0],
[2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 0],
[2, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 0],
[1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1, 0],
[2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 0],
[1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 0],
[1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 0],
[1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 2, 2, 2, 0],
[2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 2, 0],
[2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 0],
[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0],
]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3 + 1 + 3 + 3 + 2 + 1 + 2 + 5)
def test_get_score(self):
aln = Align.read("TreeConstruction/msa.phy", "phylip")
tree = Phylo.read("./TreeConstruction/upgma.tre", "newick")
scorer = ParsimonyScorer()
score = scorer.get_score(tree, aln)
self.assertEqual(score, 2 + 1 + 2 + 2 + 1 + 1 + 1 + 3)
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3.5 + 2.5 + 3.5 + 3.5 + 2.5 + 1 + 2.5 + 4.5)
alphabet = [
"A",
"C",
"D",
"E",
"F",
"G",
"H",
"I",
"K",
"L",
"M",
"N",
"P",
"Q",
"R",
"1",
"2",
"T",
"V",
"W",
"Y",
"*",
"-",
]
step_matrix = [
[0],
[2, 0],
[1, 2, 0],
[1, 2, 1, 0],
[2, 1, 2, 2, 0],
[1, 1, 1, 1, 2, 0],
[2, 2, 1, 2, 2, 2, 0],
[2, 2, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 2, 1, 0],
[2, 2, 2, 2, 1, 2, 1, 1, 2, 0],
[2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 0],
[2, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 0],
[1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1, 0],
[2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 0],
[1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 0],
[1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 0],
[1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 0],
[2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 2, 2, 2, 0],
[2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 2, 0],
[2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 0],
[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0],
]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
score = scorer.get_score(tree, aln)
self.assertEqual(score, 3 + 1 + 3 + 3 + 2 + 1 + 2 + 5)
class NNITreeSearcherTest(unittest.TestCase):
"""Test NNITreeSearcher."""
def test_get_neighbors(self):
tree = Phylo.read("./TreeConstruction/upgma.tre", "newick")
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
trees = searcher._get_neighbors(tree)
self.assertEqual(len(trees), 2 * (5 - 3))
Phylo.write(trees, os.path.join(temp_dir, "neighbor_trees.tre"), "newick")
class ParsimonyTreeConstructorTest(unittest.TestCase):
"""Test ParsimonyTreeConstructor."""
def test_build_tree_msa(self):
aln = AlignIO.read("TreeConstruction/msa.phy", "phylip")
tree1 = Phylo.read("./TreeConstruction/upgma.tre", "newick")
tree2 = Phylo.read("./TreeConstruction/nj.tre", "newick")
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
constructor = ParsimonyTreeConstructor(searcher, tree1)
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars1.tre"), "newick")
constructor.starting_tree = tree2
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars2.tre"), "newick")
constructor.starting_tree = None
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars3.tre"), "newick")
def test_build_tree(self):
aln = Align.read("TreeConstruction/msa.phy", "phylip")
tree1 = Phylo.read("./TreeConstruction/upgma.tre", "newick")
tree2 = Phylo.read("./TreeConstruction/nj.tre", "newick")
alphabet = ["A", "T", "C", "G"]
step_matrix = [[0], [2.5, 0], [2.5, 1, 0], [1, 2.5, 2.5, 0]]
matrix = _Matrix(alphabet, step_matrix)
scorer = ParsimonyScorer(matrix)
searcher = NNITreeSearcher(scorer)
constructor = ParsimonyTreeConstructor(searcher, tree1)
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars1.tre"), "newick")
constructor.starting_tree = tree2
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars2.tre"), "newick")
constructor.starting_tree = None
best_tree = constructor.build_tree(aln)
Phylo.write(best_tree, os.path.join(temp_dir, "pars3.tre"), "newick")
if __name__ == "__main__":
runner = unittest.TextTestRunner(verbosity=2)
unittest.main(testRunner=runner)
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