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# ----------------------------------------------------------------------------
# Copyright (c) 2016-2023, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
import skbio
import numpy as np
import unittest
from q2_alignment._filter import _most_conserved
from q2_alignment import mask
class MostConservedTests(unittest.TestCase):
def test_basic(self):
frequencies = [{'A': 1/3, '-': 2/3}, {'G': 1.0}, {'A': 2/3, 'C': 1/3}]
actual = _most_conserved(frequencies, skbio.DNA)
expected = [1.0, 1.0, 2./3.]
self.assertEqual(actual, expected)
frequencies = [{'A': 1/4, '-': 3/4}, {'G': 1.0}, {'A': 1/2, 'C': 1/2},
{'A': 1/4, 'C': 1/4, 'G': 1/4, 'T': 1/4}]
actual = _most_conserved(frequencies, skbio.DNA)
expected = [1.0, 1.0, 0.5, 0.25]
self.assertEqual(actual, expected)
def test_N(self):
frequencies = [{'A': 1/3, '-': 2/3}, {'G': 1.0}, {'A': 2/3, 'N': 1/3}]
actual = _most_conserved(frequencies, skbio.DNA)
expected = [1.0, 1.0, 2./3.]
self.assertEqual(actual, expected)
def test_unknown_gap_mode(self):
frequencies = [{'A': 1/3, '-': 2/3}, {'G': 1.0}, {'A': 2/3, 'C': 1/3}]
with self.assertRaises(ValueError):
_most_conserved(frequencies, skbio.DNA, gap_mode='not-real')
def test_all_gap(self):
frequencies = [{'-': 1.0}]
actual = _most_conserved(frequencies, skbio.DNA)
expected = [0.0]
self.assertEqual(actual, expected)
def test_empty(self):
frequencies = []
actual = _most_conserved(frequencies, skbio.DNA)
expected = []
self.assertEqual(actual, expected)
class MaskTests(unittest.TestCase):
def test_basic(self):
alignment = skbio.TabularMSA(
[skbio.DNA('AGA', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('-GA', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('-GC', metadata={'id': 'seq3', 'description': ''})]
)
actual = mask(alignment, max_gap_frequency=0.05, min_conservation=0.30)
expected = skbio.TabularMSA(
[skbio.DNA('GA', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('GA', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('GC', metadata={'id': 'seq3', 'description': ''})]
)
self.assertEqual(actual, expected)
def test_gap_boundaries(self):
alignment1 = skbio.TabularMSA(
[skbio.DNA('-', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq3', 'description': ''})]
)
alignment2 = skbio.TabularMSA(
[skbio.DNA('A', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('A', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('A', metadata={'id': 'seq3', 'description': ''})]
)
actual = mask(alignment1, max_gap_frequency=1.0, min_conservation=0.0)
self.assertEqual(actual, alignment1)
actual = mask(alignment2, max_gap_frequency=0.0, min_conservation=0.0)
self.assertEqual(actual, alignment2)
def test_error_on_empty_alignment_gap_boundary(self):
alignment1 = skbio.TabularMSA(
[skbio.DNA('A', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq3', 'description': ''})]
)
self.assertRaisesRegex(ValueError,
" 0.00% of positions were retained by the gap",
mask, alignment1, max_gap_frequency=0.1,
min_conservation=0.0)
def test_conservation_boundaries(self):
alignment1 = skbio.TabularMSA(
[skbio.DNA('A', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('A', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('A', metadata={'id': 'seq3', 'description': ''})])
alignment2 = skbio.TabularMSA(
[skbio.DNA('-', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq3', 'description': ''})])
actual = mask(alignment1, max_gap_frequency=1.0, min_conservation=1.0)
self.assertEqual(actual, alignment1)
actual = mask(alignment2, max_gap_frequency=1.0, min_conservation=0.0)
self.assertEqual(actual, alignment2)
def test_error_on_empty_alignment_conservation_boundary(self):
alignment1 = skbio.TabularMSA(
[skbio.DNA('A', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('C', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('G', metadata={'id': 'seq3', 'description': ''})])
self.assertRaisesRegex(ValueError,
" 0.00% of positions were retained by the con",
mask, alignment1, max_gap_frequency=1.0,
min_conservation=0.5)
def test_invalid_gap_threshold(self):
alignment = skbio.TabularMSA(
[skbio.DNA('-', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq3', 'description': ''})]
)
eps = np.finfo(float).eps
with self.assertRaises(ValueError):
mask(alignment, max_gap_frequency=0.0 - eps)
with self.assertRaises(ValueError):
mask(alignment, max_gap_frequency=1.0 + eps)
def test_invalid_conservation_threshold(self):
alignment = skbio.TabularMSA(
[skbio.DNA('-', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('-', metadata={'id': 'seq3', 'description': ''})]
)
eps = np.finfo(float).eps
with self.assertRaises(ValueError):
mask(alignment, min_conservation=0.0 - eps)
with self.assertRaises(ValueError):
mask(alignment, min_conservation=1.0 + eps)
def test_empty_input(self):
alignment = skbio.TabularMSA(
[skbio.DNA('', metadata={'id': 'seq1', 'description': ''}),
skbio.DNA('', metadata={'id': 'seq2', 'description': ''}),
skbio.DNA('', metadata={'id': 'seq3', 'description': ''})]
)
with self.assertRaises(ValueError):
mask(alignment)
alignment = skbio.TabularMSA([])
with self.assertRaises(ValueError):
mask(alignment)
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