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 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672
|
# ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
# ----------------------------------------------------------------------------
import io
import string
import unittest
import warnings
from functools import partial
from skbio import read, write, Sequence, DNA, RNA, Protein, TabularMSA
from skbio.io import FASTQFormatError
from skbio.io.format.fastq import (
_fastq_sniffer, _fastq_to_generator, _fastq_to_tabular_msa,
_generator_to_fastq, _tabular_msa_to_fastq)
from skbio.sequence._grammared_sequence import GrammaredSequence
from skbio.util import get_data_path
from skbio.util._decorator import classproperty, overrides
import numpy as np
# Note: the example FASTQ files with file extension .fastq are taken from the
# following open-access publication's supplementary data:
#
# P.J.A. Cock, C.J. Fields, N. Goto, M.L. Heuer and P.M. Rice (2009). The
# Sanger FASTQ file format for sequences with quality scores, and the
# Solexa/Illumina FASTQ variants.
#
# See licenses/fastq-example-files-readme.txt for the original README that
# accompanied these files, which includes the terms of use and detailed
# description of the files.
#
# The example files bearing the original filenames have not been modified from
# their original form.
def _drop_kwargs(kwargs, *args):
for arg in args:
if arg in kwargs:
kwargs.pop(arg)
class TestSniffer(unittest.TestCase):
def setUp(self):
self.positives = [get_data_path(e) for e in [
'fastq_multi_seq_sanger',
'fastq_multi_blank_between_records',
'fastq_multi_ws_lines_between_records',
'fastq_multi_blank_end_of_file',
'fastq_multi_ws_lines_end_of_file',
'fastq_multi_whitespace_stripping',
'fastq_blank_lines',
'fastq_whitespace_only_lines',
'fastq_single_seq_illumina1.3',
'fastq_wrapping_as_illumina_no_description',
'fastq_wrapping_as_sanger_no_description',
'fastq_wrapping_original_sanger_no_description',
'fastq_writer_illumina1.3_defaults',
'fastq_writer_sanger_defaults',
'fastq_writer_sanger_non_defaults',
'fastq_5_blanks_start_of_file',
'fastq_5_ws_lines_start_of_file',
'illumina_full_range_as_illumina.fastq',
'illumina_full_range_as_sanger.fastq',
'illumina_full_range_original_illumina.fastq',
'longreads_as_illumina.fastq',
'longreads_as_sanger.fastq',
'longreads_original_sanger.fastq',
'misc_dna_as_illumina.fastq',
'misc_dna_as_sanger.fastq',
'misc_dna_original_sanger.fastq',
'misc_rna_as_illumina.fastq',
'misc_rna_as_sanger.fastq',
'misc_rna_original_sanger.fastq',
'sanger_full_range_as_illumina.fastq',
'sanger_full_range_as_sanger.fastq',
'sanger_full_range_original_sanger.fastq',
'solexa_full_range_original_solexa.fastq',
'wrapping_as_illumina.fastq',
'wrapping_as_sanger.fastq',
'wrapping_original_sanger.fastq'
]]
self.negatives = [get_data_path(e) for e in [
'empty',
'whitespace_only',
'fastq_multi_blank_start_of_file',
'fastq_multi_ws_lines_start_of_file',
'fastq_invalid_blank_after_header',
'fastq_invalid_blank_after_seq',
'fastq_invalid_blank_after_plus',
'fastq_invalid_blank_within_seq',
'fastq_invalid_blank_within_qual',
'fastq_invalid_ws_line_after_header',
'fastq_invalid_ws_line_after_seq',
'fastq_invalid_ws_line_after_plus',
'fastq_invalid_ws_line_within_seq',
'fastq_invalid_ws_line_within_qual',
'fastq_invalid_missing_header',
'fastq_invalid_missing_seq_data',
'error_diff_ids.fastq',
'error_double_qual.fastq',
'error_double_seq.fastq',
'error_long_qual.fastq',
'error_no_qual.fastq',
'error_qual_del.fastq',
'error_qual_escape.fastq',
'error_qual_null.fastq',
'error_qual_space.fastq',
'error_qual_tab.fastq',
'error_qual_unit_sep.fastq',
'error_qual_vtab.fastq',
'error_short_qual.fastq',
'error_spaces.fastq',
'error_tabs.fastq',
'error_trunc_at_seq.fastq',
'error_trunc_at_plus.fastq',
'error_trunc_at_qual.fastq',
'error_trunc_in_title.fastq',
'error_trunc_in_seq.fastq',
'error_trunc_in_plus.fastq',
'error_trunc_in_qual.fastq',
]]
def test_positives(self):
for fp in self.positives:
self.assertEqual(_fastq_sniffer(fp), (True, {}))
def test_negatives(self):
for fp in self.negatives:
self.assertEqual(_fastq_sniffer(fp), (False, {}))
def test_illumina_sniffed(self):
fp = get_data_path('fastq_single_seq_illumina1.8')
self.assertEqual(_fastq_sniffer(fp), (True, {'variant':
'illumina1.8'}))
class TestReaders(unittest.TestCase):
def setUp(self):
self.valid_configurations = [
([get_data_path('empty'),
get_data_path('whitespace_only')],
[{},
{'variant': 'illumina1.8'},
{'phred_offset': 33,
'constructor': DNA}],
[]),
([get_data_path('fastq_single_seq_illumina1.3')], [
{'variant': 'illumina1.3'},
{'phred_offset': 64},
{'variant': 'illumina1.3',
'constructor': Protein},
], [
('', 'bar\t baz', 'aCGT', [33, 34, 35, 36])
]),
([get_data_path('fastq_multi_seq_sanger'),
get_data_path('fastq_whitespace_only_lines'),
get_data_path('fastq_blank_lines'),
get_data_path('fastq_multi_blank_between_records'),
get_data_path('fastq_multi_ws_lines_between_records'),
get_data_path('fastq_multi_blank_end_of_file'),
get_data_path('fastq_multi_ws_lines_end_of_file'),
get_data_path('fastq_multi_blank_start_of_file'),
get_data_path('fastq_multi_ws_lines_start_of_file'),
get_data_path('fastq_multi_whitespace_stripping')], [
{'variant': 'sanger'},
{'phred_offset': 33, 'seq_num': 2},
{'variant': 'sanger',
'constructor': partial(RNA, validate=False),
'seq_num': 3},
], [
('foo', 'bar baz', 'AACCGG',
[16, 17, 18, 19, 20, 21]),
('bar', 'baz foo', 'TTGGCC',
[23, 22, 21, 20, 19, 18]),
('baz', 'foo bar', 'GATTTC',
[20, 21, 22, 23, 24, 18])
]),
]
self.invalid_files = [(get_data_path(e[0]), e[1], e[2]) for e in [
('fastq_invalid_blank_after_header', FASTQFormatError,
'blank or whitespace-only line.*after header.*in FASTQ'),
('fastq_invalid_blank_after_seq', FASTQFormatError,
"blank or whitespace-only line.*before '\+' in FASTQ"),
('fastq_invalid_blank_after_plus', FASTQFormatError,
"blank or whitespace-only line.*after '\+'.*in FASTQ"),
('fastq_invalid_blank_within_seq', FASTQFormatError,
'blank or whitespace-only line.*within sequence.*FASTQ'),
('fastq_invalid_blank_within_qual', FASTQFormatError,
"blank or whitespace-only line.*within quality scores.*in FASTQ"),
('fastq_invalid_ws_line_after_header', FASTQFormatError,
'blank or whitespace-only line.*after header.*in FASTQ'),
('fastq_invalid_ws_line_after_seq', FASTQFormatError,
"blank or whitespace-only line.*before '\+' in FASTQ"),
('fastq_invalid_ws_line_after_plus', FASTQFormatError,
"blank or whitespace-only line.*after '\+'.*in FASTQ"),
('fastq_invalid_ws_line_within_seq', FASTQFormatError,
'blank or whitespace-only line.*within sequence.*FASTQ'),
('fastq_invalid_ws_line_within_qual', FASTQFormatError,
"blank or whitespace-only line.*within quality scores.*in FASTQ"),
('fastq_invalid_missing_header', FASTQFormatError,
"sequence.*header.*start of file: 'seq1 desc1'"),
('fastq_invalid_missing_seq_data', FASTQFormatError,
'without sequence data'),
('error_diff_ids.fastq', FASTQFormatError,
"header lines do not match: "
"'SLXA-B3_649_FC8437_R1_1_1_850_123' != "
"'SLXA-B3_649_FC8437_R1_1_1_850_124'"),
('error_double_qual.fastq', FASTQFormatError,
"Extra quality.*'\+SLXA-B3_649_FC8437_R1_1_1_850_123'"),
('error_double_seq.fastq', FASTQFormatError,
'FASTQ record that is missing a quality \(\+\) header line'),
('error_long_qual.fastq', FASTQFormatError, "Extra quality.*'Y'"),
('error_no_qual.fastq', FASTQFormatError,
"blank or whitespace-only line.*after '\+'.*in FASTQ"),
('error_qual_del.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_qual_escape.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_qual_null.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_qual_space.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_qual_tab.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_qual_unit_sep.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_qual_vtab.fastq', ValueError,
'Decoded Phred score.*out of range'),
('error_short_qual.fastq', FASTQFormatError,
"Extra quality.*'SLXA-B3_649_FC8437_R1_1_1_362_549'"),
('error_spaces.fastq', FASTQFormatError,
"whitespace.*sequence data: 'GATGTGCAA TACCTTTGTA GAGGAA'"),
('error_tabs.fastq', FASTQFormatError,
r"whitespace.*sequence data: 'GATGTGCAA\\tTACCTTTGTA\\tGAGGAA'"),
('error_trunc_at_seq.fastq', FASTQFormatError,
'incomplete/truncated.*FASTQ'),
('error_trunc_at_plus.fastq', FASTQFormatError,
'incomplete/truncated.*FASTQ'),
('error_trunc_at_qual.fastq', FASTQFormatError,
'incomplete/truncated.*end of file'),
('error_trunc_in_title.fastq', FASTQFormatError,
'incomplete/truncated.*end of file'),
('error_trunc_in_seq.fastq', FASTQFormatError,
'incomplete/truncated.*end of file'),
('error_trunc_in_plus.fastq', FASTQFormatError,
"header lines do not match: "
"'SLXA-B3_649_FC8437_R1_1_1_183_714' != 'SLXA-B3_649_FC'"),
('error_trunc_in_qual.fastq', FASTQFormatError,
'incomplete/truncated.*end of file')
]]
def test_fastq_to_generator_valid_files(self):
for valid_files, kwargs, components in self.valid_configurations:
for valid in valid_files:
for observed_kwargs in kwargs:
_drop_kwargs(observed_kwargs, 'seq_num')
constructor = observed_kwargs.get('constructor', Sequence)
expected_kwargs = {}
expected_kwargs['lowercase'] = 'introns'
observed_kwargs['lowercase'] = 'introns'
expected = [constructor(c[2],
metadata={'id': c[0],
'description': c[1]},
positional_metadata={'quality': np.array(c[3],
dtype=np.uint8)},
**expected_kwargs)
for c in components]
observed = list(_fastq_to_generator(valid,
**observed_kwargs))
self.assertEqual(len(expected), len(observed))
for o, e in zip(observed, expected):
self.assertEqual(o, e)
def test_fastq_to_generator_invalid_files_all_variants(self):
# files that should be invalid for all variants, as well as custom
# phred offsets
for fp, error_type, error_msg_regex in self.invalid_files:
for variant in 'sanger', 'illumina1.3', 'illumina1.8':
with self.assertRaisesRegex(error_type, error_msg_regex):
list(_fastq_to_generator(fp, variant=variant))
for offset in 33, 64, 40, 77:
with self.assertRaisesRegex(error_type, error_msg_regex):
list(_fastq_to_generator(fp, phred_offset=offset))
def test_fastq_to_generator_invalid_files_illumina(self):
# files that should be invalid for illumina1.3 and illumina1.8 variants
fps = [get_data_path(fp) for fp in
['sanger_full_range_original_sanger.fastq',
'solexa_full_range_original_solexa.fastq']]
for fp in fps:
with self.assertRaisesRegex(ValueError, 'out of range \[0, 62\]'):
list(_fastq_to_generator(fp, variant='illumina1.3'))
with self.assertRaisesRegex(ValueError, 'out of range \[0, 62\]'):
list(_fastq_to_generator(fp, variant='illumina1.8'))
def test_fastq_to_generator_solexa(self):
# solexa support isn't implemented yet. should raise error even with
# valid solexa file
with self.assertRaisesRegex(ValueError, 'Solexa'):
list(_fastq_to_generator(
get_data_path('solexa_full_range_original_solexa.fastq'),
variant='solexa'))
def test_fastq_to_sequence(self):
for constructor in [Sequence, DNA, RNA, Protein]:
for valid_files, kwargs, components in self.valid_configurations:
for valid in valid_files:
# skip empty file case since we cannot read a specific
# sequencefrom an empty file
if len(components) == 0:
continue
for observed_kwargs in kwargs:
expected_kwargs = {}
# TODO:
# some of the test files contain characters which are
# invalid for RNA, so don't validate for now. Need to
# fix this
if constructor is RNA:
observed_kwargs['validate'] = False
expected_kwargs['validate'] = False
_drop_kwargs(observed_kwargs, 'constructor')
expected_kwargs['lowercase'] = 'introns'
observed_kwargs['lowercase'] = 'introns'
seq_num = observed_kwargs.get('seq_num', 1)
c = components[seq_num - 1]
expected = \
constructor(
c[2], metadata={'id': c[0],
'description': c[1]},
positional_metadata={'quality': np.array(c[3],
dtype=np.uint8)},
**expected_kwargs)
observed = read(valid, into=constructor,
format='fastq', verify=False,
**observed_kwargs)
self.assertEqual(observed, expected)
def test_fastq_to_tabular_msa(self):
class CustomSequence(GrammaredSequence):
@classproperty
@overrides(GrammaredSequence)
def gap_chars(cls):
return set('-.')
@classproperty
@overrides(GrammaredSequence)
def default_gap_char(cls):
return '-'
@classproperty
@overrides(GrammaredSequence)
def definite_chars(cls):
return set(string.ascii_letters)
@classproperty
@overrides(GrammaredSequence)
def degenerate_map(cls):
return {}
for valid_files, kwargs, components in self.valid_configurations:
for valid in valid_files:
for observed_kwargs in kwargs:
_drop_kwargs(observed_kwargs, 'seq_num')
if 'constructor' not in observed_kwargs:
observed_kwargs['constructor'] = CustomSequence
constructor = observed_kwargs['constructor']
expected_kwargs = {}
expected_kwargs['lowercase'] = 'introns'
observed_kwargs['lowercase'] = 'introns'
expected = TabularMSA(
[constructor(
c[2], metadata={'id': c[0],
'description': c[1]},
positional_metadata={'quality': np.array(c[3],
dtype=np.uint8)},
**expected_kwargs)
for c in components])
observed = _fastq_to_tabular_msa(valid, **observed_kwargs)
self.assertEqual(observed, expected)
def test_fastq_to_tabular_msa_no_constructor(self):
with self.assertRaisesRegex(ValueError, '`constructor`'):
_fastq_to_tabular_msa(get_data_path('fastq_multi_seq_sanger'))
class TestWriters(unittest.TestCase):
def setUp(self):
self.valid_files = [
([
('f o o', 'bar\n\nbaz', 'AaCcGg',
[16, 17, 18, 19, 20, 21]),
('bar', 'baz foo', 'TtGgCc',
[23, 22, 21, 20, 19, 18]),
('ba\n\t\tz', 'foo bar', 'gAtTtC',
[20, 21, 22, 23, 24, 18])
], [
({'variant': 'sanger'},
get_data_path('fastq_writer_sanger_defaults')),
({'phred_offset': 33},
get_data_path('fastq_writer_sanger_defaults')),
({'variant': 'illumina1.8'},
get_data_path('fastq_writer_sanger_defaults')),
({'variant': 'illumina1.3'},
get_data_path('fastq_writer_illumina1.3_defaults')),
({'variant': 'sanger', 'id_whitespace_replacement': '%',
'description_newline_replacement': '^'},
get_data_path('fastq_writer_sanger_non_defaults'))
]),
]
def test_generator_to_fastq_kwargs_passed(self):
for components, kwargs_expected_fp in self.valid_files:
for kwargs, expected_fp in kwargs_expected_fp:
def gen():
for c in components:
yield Sequence(
c[2], metadata={'id': c[0], 'description': c[1]},
positional_metadata={'quality': c[3]})
fh = io.StringIO()
_generator_to_fastq(gen(), fh, **kwargs)
observed = fh.getvalue()
fh.close()
with io.open(expected_fp) as f:
expected = f.read()
self.assertEqual(observed, expected)
def test_sequence_to_fastq_kwargs_passed(self):
for constructor in [Sequence, DNA, RNA, Protein]:
for components, kwargs_expected_fp in self.valid_files:
for expected_kwargs, expected_fp in kwargs_expected_fp:
observed_kwargs = {}
# TODO:
# some of the test files contain characters which are
# invalid for RNA, so don't validate for now. Need to
# fix this
if constructor is RNA:
observed_kwargs['validate'] = False
expected_kwargs['lowercase'] = 'introns'
observed_kwargs['lowercase'] = 'introns'
fh = io.StringIO()
for c in components:
obj = constructor(
c[2],
metadata={'id': c[0], 'description': c[1]},
positional_metadata={'quality': c[3]},
**observed_kwargs)
write(obj, into=fh, format='fastq', **expected_kwargs)
observed = fh.getvalue()
fh.close()
with io.open(expected_fp) as f:
expected = f.read()
self.assertEqual(observed, expected)
def test_tabular_msa_to_fastq_kwargs_passed(self):
for components, kwargs_expected_fp in self.valid_files:
for kwargs, expected_fp in kwargs_expected_fp:
obj = TabularMSA([
Protein(c[2], metadata={'id': c[0], 'description': c[1]},
positional_metadata={'quality': c[3]},
lowercase='introns')
for c in components])
fh = io.StringIO()
kwargs['lowercase'] = 'introns'
_tabular_msa_to_fastq(obj, fh, **kwargs)
observed = fh.getvalue()
fh.close()
with io.open(expected_fp) as f:
expected = f.read()
self.assertEqual(observed, expected)
def test_generator_to_fastq_no_qual(self):
def gen():
yield Sequence('ACGT',
metadata={'id': 'foo', 'description': 'bar'},
positional_metadata={'quality': range(4)})
yield Sequence('ACG', metadata={'id': 'foo', 'description': 'bar'})
with self.assertRaisesRegex(ValueError, '2nd.*quality scores'):
_generator_to_fastq(gen(), io.StringIO(), variant='illumina1.8')
class TestConversions(unittest.TestCase):
def setUp(self):
self.conversions = [
(get_data_path('empty'),
get_data_path('empty'), [
({'variant': 'sanger'}, {'phred_offset': 42}),
]),
(get_data_path('longreads_original_sanger.fastq'),
get_data_path('longreads_as_sanger.fastq'), [
({'variant': 'sanger'}, {'variant': 'sanger'}),
({'phred_offset': 33}, {'variant': 'sanger'}),
({'variant': 'sanger'}, {'phred_offset': 33})
]),
(get_data_path('longreads_original_sanger.fastq'),
get_data_path('longreads_as_illumina.fastq'), [
({'variant': 'sanger'}, {'variant': 'illumina1.3'}),
({'phred_offset': 33}, {'variant': 'illumina1.3'}),
({'variant': 'sanger'}, {'phred_offset': 64})
]),
(get_data_path('wrapping_original_sanger.fastq'),
get_data_path('wrapping_as_sanger.fastq'), [
({'variant': 'sanger'}, {'variant': 'sanger'}),
({'phred_offset': 33}, {'variant': 'sanger'}),
({'variant': 'sanger'}, {'phred_offset': 33})
]),
(get_data_path('wrapping_original_sanger.fastq'),
get_data_path('wrapping_as_illumina.fastq'), [
({'variant': 'sanger'}, {'variant': 'illumina1.3'}),
({'phred_offset': 33}, {'variant': 'illumina1.3'}),
({'variant': 'sanger'}, {'phred_offset': 64})
]),
(get_data_path('sanger_full_range_original_sanger.fastq'),
get_data_path('sanger_full_range_as_sanger.fastq'), [
({'variant': 'sanger'}, {'variant': 'sanger'}),
({'phred_offset': 33}, {'variant': 'sanger'}),
({'variant': 'sanger'}, {'phred_offset': 33})
]),
(get_data_path('sanger_full_range_original_sanger.fastq'),
get_data_path('sanger_full_range_as_illumina.fastq'), [
({'variant': 'sanger'}, {'variant': 'illumina1.3'}),
({'phred_offset': 33}, {'variant': 'illumina1.3'}),
({'variant': 'sanger'}, {'phred_offset': 64})
]),
(get_data_path('illumina_full_range_original_illumina.fastq'),
get_data_path('illumina_full_range_as_illumina.fastq'), [
({'variant': 'illumina1.3'}, {'variant': 'illumina1.3'}),
({'phred_offset': 64}, {'variant': 'illumina1.3'}),
({'variant': 'illumina1.3'}, {'phred_offset': 64})
]),
(get_data_path('illumina_full_range_original_illumina.fastq'),
get_data_path('illumina_full_range_as_sanger.fastq'), [
({'variant': 'illumina1.3'}, {'variant': 'sanger'}),
({'phred_offset': 64}, {'variant': 'sanger'}),
({'variant': 'illumina1.3'}, {'phred_offset': 33})
]),
(get_data_path('misc_dna_original_sanger.fastq'),
get_data_path('misc_dna_as_sanger.fastq'), [
({'variant': 'sanger'}, {'variant': 'sanger'}),
({'phred_offset': 33}, {'variant': 'sanger'}),
({'variant': 'sanger'}, {'phred_offset': 33})
]),
(get_data_path('misc_dna_original_sanger.fastq'),
get_data_path('misc_dna_as_illumina.fastq'), [
({'variant': 'sanger'}, {'variant': 'illumina1.3'}),
({'phred_offset': 33}, {'variant': 'illumina1.3'}),
({'variant': 'sanger'}, {'phred_offset': 64})
]),
(get_data_path('misc_rna_original_sanger.fastq'),
get_data_path('misc_rna_as_sanger.fastq'), [
({'variant': 'sanger'}, {'variant': 'sanger'}),
({'phred_offset': 33}, {'variant': 'sanger'}),
({'variant': 'sanger'}, {'phred_offset': 33})
]),
(get_data_path('misc_rna_original_sanger.fastq'),
get_data_path('misc_rna_as_illumina.fastq'), [
({'variant': 'sanger'}, {'variant': 'illumina1.3'}),
({'phred_offset': 33}, {'variant': 'illumina1.3'}),
({'variant': 'sanger'}, {'phred_offset': 64})
]),
(get_data_path('fastq_wrapping_original_sanger_no_description'),
get_data_path('fastq_wrapping_as_sanger_no_description'), [
({'variant': 'sanger'}, {'variant': 'sanger'}),
({'phred_offset': 33}, {'variant': 'sanger'}),
({'variant': 'sanger'}, {'phred_offset': 33})
]),
(get_data_path('fastq_wrapping_original_sanger_no_description'),
get_data_path('fastq_wrapping_as_illumina_no_description'), [
({'variant': 'sanger'}, {'variant': 'illumina1.3'}),
({'phred_offset': 33}, {'variant': 'illumina1.3'}),
({'variant': 'sanger'}, {'phred_offset': 64})
]),
]
def test_conversion(self):
for from_fp, to_fp, kwargs in self.conversions:
for from_kwargs, to_kwargs in kwargs:
read_gen = _fastq_to_generator(from_fp, **from_kwargs)
fh = io.StringIO()
# will issue warning when truncating quality scores
with warnings.catch_warnings(record=True):
warnings.simplefilter("ignore")
_generator_to_fastq(read_gen, fh, **to_kwargs)
obs = fh.getvalue()
fh.close()
with io.open(to_fp) as fh:
exp = fh.read()
self.assertEqual(obs, exp)
if __name__ == '__main__':
unittest.main()
|