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#!/usr/bin/env python
import itertools
import unittest
import cogent3.align.progressive
import cogent3.evolve.substitution_model
from cogent3 import DNA, make_unaligned_seqs
from cogent3.align.align import (
classic_align_pairwise,
global_pairwise,
local_pairwise,
make_dna_scoring_dict,
make_generic_scoring_dict,
)
from cogent3.evolve.models import HKY85, get_model
dna_model = cogent3.evolve.substitution_model.TimeReversibleNucleotide(
model_gaps=False, equal_motif_probs=True
)
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2022, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley", "Rob Knight"]
__license__ = "BSD-3"
__version__ = "2023.2.12a1"
__maintainer__ = "Gavin Huttley"
__email__ = "gavin.huttley@anu.edu.au"
__status__ = "Production"
def matchedColumns(align):
"""Count the matched columns in an alignment"""
def all_same(column):
consensus = None
for motif in column:
if consensus is None:
consensus = motif
elif motif != consensus:
return False
return True
return len(align.filtered(all_same))
seq1 = DNA.make_seq("aaaccggacattacgtgcgta", name="FAKE01")
seq2 = DNA.make_seq("ccggtcaggttacgtacgtt", name="FAKE02")
class AlignmentTestCase(unittest.TestCase):
def _aligned_both_ways(self, seq1, seq2, **kw):
S = make_dna_scoring_dict(10, -1, -8)
a1 = classic_align_pairwise(seq1, seq2, S, 10, 2, **kw)
a2 = classic_align_pairwise(seq2, seq1, S, 10, 2, **kw)
return [a1, a2]
def test_local(self):
for a in self._aligned_both_ways(seq1, seq2, local=True):
self.assertEqual(matchedColumns(a), 15)
self.assertEqual(len(a), 19)
def test_pwise_protein(self):
"""works for pairwise protein alignment"""
from cogent3 import PROTEIN
S = make_generic_scoring_dict(1, PROTEIN)
seq1 = PROTEIN.make_seq("MAYPFQLGLQD", "seq1")
seq2 = PROTEIN.make_seq("MAYPFGLQD", "seq2")
a1 = classic_align_pairwise(seq1, seq2, S, 10, 2, local=False)
self.assertEqual(a1.to_dict(), dict(seq1="MAYPFQLGLQD", seq2="MAYPF--GLQD"))
def test_gap_at_one_end(self):
for a in self._aligned_both_ways(seq1, seq2, local=False):
self.assertEqual(matchedColumns(a), 15)
self.assertEqual(len(a), 23)
def test_gaps_at_both_ends(self):
s = "aaaccggttt"
s1 = DNA.make_seq(s[:-2], name="A")
s2 = DNA.make_seq(s[2:], name="B")
for a in self._aligned_both_ways(s1, s2, local=False):
self.assertEqual(matchedColumns(a), 6)
self.assertEqual(len(a), 10)
def test_short(self):
s1 = DNA.make_seq("tacagta", name="A")
s2 = DNA.make_seq("tacgtc", name="B")
for a in self._aligned_both_ways(s1, s2, local=False):
self.assertEqual(matchedColumns(a), 5)
self.assertEqual(len(a), 7)
def test_pairwise_returns_score(self):
"""exercise pairwise local/global returns alignment score"""
S = make_dna_scoring_dict(10, -1, -8)
aln, score = local_pairwise(seq1, seq2, S, 10, 2, return_score=True)
self.assertTrue(score > 100)
aln, score = global_pairwise(seq1, seq2, S, 10, 2, return_score=True)
self.assertTrue(score > 100)
def test_codon(self):
s1 = DNA.make_seq("tacgccgta", name="A")
s2 = DNA.make_seq("tacgta", name="B")
codon_model = cogent3.evolve.substitution_model.TimeReversibleCodon(
model_gaps=False, equal_motif_probs=True, mprob_model="conditional"
)
tree = cogent3.make_tree(tip_names=["A", "B"])
lf = codon_model.make_likelihood_function(tree, aligned=False)
lf.set_sequences(dict(A=s1, B=s2))
a = lf.get_log_likelihood().edge.get_viterbi_path().get_alignment()
self.assertEqual(matchedColumns(a), 6)
self.assertEqual(len(a), 9)
def test_local_tiebreak(self):
"""Should pick the first best-equal hit rather than the last one"""
# so that the Pyrex and Python versions give the same result.
score_matrix = make_dna_scoring_dict(match=1, transition=-1, transversion=-1)
pattern = DNA.make_seq("cwc", name="pattern")
two_hit = DNA.make_seq("cactc", name="target")
aln = local_pairwise(pattern, two_hit, score_matrix, 5, 2)
hit = aln.named_seqs["target"]
self.assertEqual(str(hit).lower(), "cac")
class UnalignedPairTestCase(unittest.TestCase):
def test_forward(self):
tree = cogent3.make_tree(tip_names="AB")
pc = dna_model.make_likelihood_function(tree, aligned=False)
pc.set_sequences({"A": seq1, "B": seq2})
LnL = pc.get_log_likelihood()
assert isinstance(LnL, float)
class MultipleAlignmentTestCase(unittest.TestCase):
def _make_aln(
self,
orig,
model=dna_model,
param_vals=None,
indel_rate=0.1,
indel_length=0.5,
**kw,
):
kw["indel_rate"] = indel_rate
kw["indel_length"] = indel_length
seqs = {key: DNA.make_seq(value) for (key, value) in list(orig.items())}
if len(seqs) == 2:
tree = cogent3.make_tree(treestring="(A:.1,B:.1)")
else:
tree = cogent3.make_tree(treestring="(((A:.1,B:.1):.1,C:.1):.1,D:.1)")
aln, tree = cogent3.align.progressive.TreeAlign(
model, seqs, tree=tree, param_vals=param_vals, show_progress=False, **kw
)
return aln
def _test_aln(self, seqs, model=dna_model, param_vals=None, **kw):
orig = {n: s.replace("-", "") for (n, s) in list(seqs.items())}
aln = self._make_aln(orig, model=model, param_vals=param_vals, **kw)
result = {n: s.lower() for (n, s) in list(aln.to_dict().items())}
# assert the alignment result is correct
self.assertEqual(seqs, result)
# and the moltype matches the model
model = get_model(model)
self.assertIs(aln.moltype, model.moltype)
# assert the returned alignment has the correct parameter values in the
# align.info object.
if param_vals:
for param, val in param_vals:
self.assertEqual(aln.info.align_params[param], val)
def test_progressive1(self):
"""test progressive alignment, gaps in middle"""
self._test_aln(
{"A": "tacagta", "B": "tac-gtc", "C": "ta---ta", "D": "tac-gtc"},
model="F81",
)
def test_progessive_model_name(self):
"""TreeAlign handles models specified by name"""
self._test_aln({"A": "tacagta", "B": "tac-gtc", "C": "ta---ta", "D": "tac-gtc"})
def test_progressive_est_tree(self):
"""exercise progressive alignment without a guide tree"""
seqs = make_unaligned_seqs(
data={
"A": "TGTGGCACAAATGCTCATGCCAGCTCTTTACAGCATGAGAACA",
"B": "TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT",
"C": "TGTGGCACAAGTACTCATGCCAGCTCAGTACAGCATGAGAACAGCAGTTT",
}
)
aln, tree = cogent3.align.progressive.TreeAlign(
HKY85(), seqs, show_progress=False, param_vals={"kappa": 4.0}
)
expect = {
"A": "TGTGGCACAAATGCTCATGCCAGCTCTTTACAGCATGAGAACA-------",
"C": "TGTGGCACAAGTACTCATGCCAGCTCAGTACAGCATGAGAACAGCAGTTT",
"B": "TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT",
}
self.assertEqual(aln.to_dict(), expect)
aln, tree = cogent3.align.progressive.TreeAlign(
HKY85(),
seqs,
show_progress=False,
ests_from_pairwise=True,
)
expect = {
"A": "TGTGGCACAAATGCTCATGCCAGCTCTTTACAGCATGAGAACA-------",
"C": "TGTGGCACAAGTACTCATGCCAGCTCAGTACAGCATGAGAACAGCAGTTT",
"B": "TGTGGCACAGATACTCATGCCAGCTCATTACAGCATGAGAACAGCAGTTT",
}
self.assertEqual(aln.to_dict(), expect)
def test_align_info(self):
"""alignment info object has parameter values"""
aln = self._make_aln(
{"A": "gcctcgg", "B": "gcctcgg", "C": "gcctcggaaacgt", "D": "aaacgt"}
)
self.assertTrue(aln.info["align_params"]["lnL"] < 0)
def test_progressive_params(self):
"""excercise progressive alignment providing model params"""
self._test_aln(
{"A": "tacagta", "B": "tac-gtc", "C": "ta---ta", "D": "cac-cta"},
model=HKY85(),
param_vals=[("kappa", 2.0)],
)
def test_TreeAlign_does_pairs(self):
"""test TreeAlign handles pairs of sequences"""
self._test_aln({"A": "acttgtac", "B": "ac--gtac"})
def test_gap_at_start(self):
"""test progressive alignment, gaps at start"""
self._test_aln({"A": "-ac", "B": "-ac", "C": "-ac", "D": "gac"})
def test_gap_at_end(self):
"""test progressive alignment, gaps at end"""
self._test_aln({"A": "gt-", "B": "gt-", "C": "gt-", "D": "gta"})
def test_gaps2(self):
"""gaps have real costs, even end gaps"""
self._test_aln({"A": "g-", "B": "g-", "C": "ga", "D": "a-"})
self._test_aln({"A": "-g", "B": "-g", "C": "ag", "D": "-a"})
def test_difficult_end_gaps(self):
self._test_aln({"A": "--cctc", "B": "--cctc", "C": "gacctc", "D": "ga----"})
self._test_aln(
{
"A": "gcctcgg------",
"B": "gcctcgg------",
"C": "gcctcggaaacgt",
"D": "-------aaacgt",
}
)
def test_tree_align_handles_zero_lengths(self):
seqs = make_unaligned_seqs(
data={
"A": "TTAATTTTAGTAGTGCTATCCCC",
"B": "TTAATTTTAGTAGTGCTATCCCA",
"C": "TTAATTTTAGTAGTGCTATCC",
},
moltype="dna",
)
expected = {
"A": "TTAATTTTAGTAGTGCTATCCCC",
"B": "TTAATTTTAGTAGTGCTATCCCA",
"C": "TTAATTTTAGTAGTGCTATCC--",
}
tree_mapping = [
"A: 0.0225400070648391",
"B: 0.0225400070648391",
"C: 0.0",
]
tree_variants = itertools.permutations(tree_mapping, r=3)
for tree_encoding in tree_variants:
aln, _ = cogent3.align.progressive.TreeAlign(
model="F81",
seqs=seqs,
tree=cogent3.make_tree("({},{},{})".format(*tree_encoding)),
show_progress=False,
)
self.assertEqual(aln.to_dict(), expected)
class HirschbergTestCase(MultipleAlignmentTestCase):
# Force use of linear space algorithm
def _test_aln(self, seqs, **kw):
tmp = cogent3.align.pairwise.HIRSCHBERG_LIMIT
try:
cogent3.align.pairwise.HIRSCHBERG_LIMIT = 100
result = MultipleAlignmentTestCase._test_aln(self, seqs, **kw)
finally:
cogent3.align.pairwise.HIRSCHBERG_LIMIT = tmp
return result
if __name__ == "__main__":
unittest.main()
|
