def test_make_short_var():
l = 6
var = "ABCDEFGH"
hh = HtmlHandler(long_len=l)
res = hh.make_short_var(var)
expected = "ABC 2 FGH"
eq_(expected, res)
var = "ABCFGH"
res = hh.make_short_var(var)
expected = "ABCFGH"
eq_(expected, res)
def test_find_residues_neighbouring_insertions():
gold_aln_cores = {
"1ABCA": ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10'],
"1ABCB": ['2', '3', '4', '5', '-', '7', '8', '9', '10', '11'],
"1ABCC": ['-', '3', '4', '-', '-', '7', '8', '9', '10', '11'],
}
expected = {
"1ABCA": [],
"1ABCB": ['5', '7'],
"1ABCC": ['3', '4', '7'],
}
hh = HtmlHandler()
result = hh.find_residues_neighbouring_insertions(gold_aln_cores)
eq_(result, expected)
def test_make_corvar():
aa_aln = {'1': "ABCDEFGHIJKLMNOP"}
num_aln = {
'cores': {
'1': [
[2],
[6, 7, 8],
[9, 10, 11]
],
},
'var': {
'1': [[1], [3, 4, 5],
[12, 13, 14, 15, 16]]
}
}
expected = {
'1': {
'cores':
[
"B",
"FGH",
"IJK"
],
'var': [
"A",
"CDE",
"LMNOP"
]}}
hh = HtmlHandler()
res = hh.make_corvar(aa_aln, num_aln)
eq_(res, expected)
#num_aln = {'var': {'1NDDA': [], '3UF8A': [1, 2, 3, 4, 34, 35, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192]}, 'cores': {'1NDDA': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74], '3UF8A': [5, 6, 7, 8, 9, 10, 11, 12, 13, '-', 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, '-', '-', 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, '-', '-', '-']}}
full_seq = {
'1NDDA':
'MLIKVKTLTGKEIEIDIEPTDKVERIKERVEEKEGIPPQQQRLIYSGKQMNDEKTAADYKILGGSVLHLVLALR',
'3UF8A':
'PETHINLKVSDGSSEIFFKIKKTTPLRRLMEAFAKRQGKEMDSLRFLYDGIRIQADQTPEDLDMEDNDIIEAHREQIGGSTVVTTESGLKYEDLTEGSGAEARAGQTVSVHYTGWLTDGQKFDSSKDRNDPFAFVLGGGMVIKGWDEGVQGMKVGGVRRLTIPPQLGYGARGAAGVIPPNATLVFEVELLDV'
}
res = hh.make_corvar(aa_aln, num_aln)
print res
def test_get_full_seq_pos():
hh = HtmlHandler()
merged_corvar_seq = "vhINLKVKGQDGNEVFFRIKRSTQMRKLMNAY----SVDMNSIAFLFDGRRLRAEQTPDELEMEEGDEIDAMLH--"
corvar_index = 0
expected_pos = 2
pos = hh.get_full_seq_pos(merged_corvar_seq, corvar_index)
eq_(pos, expected_pos)
corvar_index = 67
expected_pos = 65
pos = hh.get_full_seq_pos(merged_corvar_seq, corvar_index)
eq_(pos, expected_pos)
merged_corvar_seq = "pethINLKVSDGS-SEI"
corvar_index = 10
expected_pos = 13
pos = hh.get_full_seq_pos(merged_corvar_seq, corvar_index)
eq_(pos, expected_pos)
merged_corvar_seq = "pethINLKVSDGS-SEIFFKIKKTTPLRRLMEAF--RQGKEMDSLRFLYDGIRIQADQTPEDLDMEDNDIIEAHR---"
corvar_index = 32
expected_pos = 35
pos = hh.get_full_seq_pos(merged_corvar_seq, corvar_index)
eq_(pos, expected_pos)
def test_split_vars():
num_aln = {
'var': {'1': [1, 4, 9, 10]},
'cores': {'1': [[2, 3], ['-'], ['-', 5, 6], [7, 8]]}
}
expected = {
'var': {'1': [[1], [], [4], [], [9, 10]]},
'cores': {'1': [[2, 3], ['-'], ['-', 5, 6], [7, 8]]}
}
hh = HtmlHandler()
res = hh.split_vars(num_aln)
eq_(expected, res)
num_aln = {
'var': {'1': [4]},
'cores': {'1': [[1, 2, 3], [5, 6], [7, 8]]}
}
expected = {
'var': {'1': [[], [4], [], []]},
'cores': {'1': [[1, 2, 3], [5, 6], [7, 8]]}
}
res = hh.split_vars(num_aln)
eq_(expected, res)
def test_calc_alignment_quality_complex():
# testcase 1 - basic, all good
gold_json_path = "gold_standard_src/tests/testdata/complex_scoring/gold_tauto.json"
# gold_corvar_path = "gold_standard_src/tests/testdata/complex_scoring/gold_tauto.txt.Var"
aln_path = "gold_standard_src/tests/testdata/complex_scoring/tautomerase_final_core.txt"
paths = {"gold_path": gold_json_path, "aln_path": aln_path}
# gold_in = parse_gold_json(gold_path, corvar_path)
output = "gold_standard_src/tests/testdata/complex_scoring/tautomerase_final_core.txt_out"
in_format = "3SSP"
calc_result = calculate_aln_quality_complex(paths,
output,
in_format,
write_json=True)
# create html output
hh = HtmlHandler()
hh.write_html(calc_result, "tmp", complex_scoring=True)
# test case 2 - two solutions for first residue of 3ABFA - can be aligned
# either with 1 or 2 (each gets 0.5 score)
# gold_json_path = "gold_standard_src/tests/testdata/complex_scoring/gold_tauto_m5.json"
aln_path = "gold_standard_src/tests/testdata/complex_scoring/tautomerase_final_core_alternative.txt"
paths = {"gold_path": gold_json_path, "aln_path": aln_path}
# gold_in = parse_gold_json(gold_path, corvar_path)
output = "gold_standard_src/tests/testdata/complex_scoring/tautomerase_final_core.txt_out"
calc_result2 = calculate_aln_quality_complex(paths,
output,
in_format,
write_json=True)
# create html output
hh = HtmlHandler()
hh.write_html(calc_result2, "tmp2", complex_scoring=True)
expected_overall = 0.82642
#ok_(abs(calc_result2["overall_score"] - expected_overall) < 0.0001)
# check if all residues in 3M21A are incorrectcly aligned
all_incorrect = [
not i[0]
for k, i in calc_result2["per_residue_scores"]["3M21A"].iteritems()
]
ok_(all_incorrect)
def run_comparison(aln1_path, aln2_path, outprefix, full_seq_path):
aln_dict1 = parse_fasta(aln1_path)
aln_dict2 = parse_fasta(aln2_path)
full_seq = parse_fasta(full_seq_path)
core_indexes = None
num_aln_dict1 = core_aln_to_num(aln_dict1, full_seq, core_indexes)[0]
num_aln_dict2 = core_aln_to_num(aln_dict2, full_seq, core_indexes)[0]
comp_result = compare_alignments(num_aln_dict1, num_aln_dict2)
hh = HtmlHandler()
quality_data = {
'aa_aln': aln_dict1,
'wrong_cols': comp_result['diff_cols1']
}
hh.write_html(quality_data, outprefix + '1')
quality_data = {
'aa_aln': aln_dict2,
'wrong_cols': comp_result['diff_cols2']
}
hh.write_html(quality_data, outprefix + '2')
def test_aln_to_html_var():
aa_aln = {'1': 'ACDEFGKLMNOP',
'2': 'ABC---DEF---'}
wrong = {'1': {0: 1, 10: 1, 11: 1}, '2': {}}
full_seq = {'1': 'ABCDEFGHIJKLMNOP',
'2': 'ABCDEF'}
num_aln, core_indexes = core_aln_to_num(aa_aln, full_seq)
expected = "1 <span class=featWRONG3>A</span> b <span class=featOK>C" \
"</span><span class=featOK>D</span><span class=featOK>E</span>" \
"<span class=featOK>F</span><span class=featOK>G</span> hij <s" \
"pan class=featOK>K</span><span class=featOK>L</span><span cla" \
"ss=featOK>M</span><span class=featOK>N</span><span class=feat" \
"WRONG3>O</span><span class=featWRONG3>P</span> \n2 <span" \
" class=featOK>A</span> <span class=featOK>B</span><span cla" \
"ss=featOK>C</span>--- <span class=featOK>D</span><span cl" \
"ass=featOK>E</span><span class=featOK>F</span>--- \n"
hh = HtmlHandler()
quality_data = {'num_aln': num_aln,
'aa_aln': aa_aln,
'wrong_cols': wrong,
'full': full_seq,
'core_indexes': core_indexes}
res = hh.aln_to_html_var(quality_data)
eq_(res, expected)
expected_path = "gold_standard_src/tests/testdata/expected.html"
with open(expected_path) as a:
expected = a.read()
expected_excerpt = expected.splitlines()[3:]
res_path = "gold_standard_src/tests/testdata/test.html"
hh.var = True
hh.write_html(quality_data, "gold_standard_src/tests/testdata/test")
ok_(os.path.exists(res_path))
with open(res_path) as a:
res = a.read()
result_excerpt = res.splitlines()[3:]
os.remove(res_path)
eq_(expected_excerpt, result_excerpt)