def test_deblur_with_non_default_error_profile(self):
error_dist = [
1, 0.05, 0.000005, 0.000005, 0.000005, 0.000005, 0.0000025,
0.0000025, 0.0000025, 0.0000025, 0.0000025, 0.0000005, 0.0000005,
0.0000005, 0.0000005
]
seqs_f = StringIO(TEST_SEQS_2)
obs = deblur(sequence_generator(seqs_f), error_dist=error_dist)
exp = [
Sequence(
"E.Coli-999;size=720;",
"tacggagggtgcaagcgttaatcggaattactgggcgtaaagcgcacgcaggcggt"
"ttgttaagtcagatgtgaaatccccgggctcaacctgggaactgcatctgatactg"
"gcaagcttgagtctcgtagaggggggcagaattccag")
]
self.assertEqual(obs, exp)
error_dist = np.array([
1, 0.06, 0.02, 0.02, 0.01, 0.005, 0.005, 0.005, 0.001, 0.001,
0.001, 0.0005
])
seqs_f = StringIO(TEST_SEQS_2)
obs = deblur(sequence_generator(seqs_f), error_dist=error_dist)
exp = [
Sequence(
"E.Coli-999;size=720;",
"tacggagggtgcaagcgttaatcggaattactgggcgtaaagcgcacgcaggcggt"
"ttgttaagtcagatgtgaaatccccgggctcaacctgggaactgcatctgatactg"
"gcaagcttgagtctcgtagaggggggcagaattccag")
]
self.assertEqual(obs, exp)
def compare_result(self, simfilename, origfilename, trim_length):
"""Compare the results of deblurring to the original mixture
Parameters
----------
simfilename : str
name of the simulated reads fasta file
origfilename : str
name of the fasta file with the ground truth sequences
trim_length : int
the length used for trimming the sequences in deblurring
"""
# get the trimmed ground truth sequences
orig_seqs = [item[1] for item in sequence_generator(origfilename)]
orig_seqs = [item[:trim_length].upper() for item in orig_seqs]
# get the deblurred fasta file sequences
out_seqs = [item[1] for item in sequence_generator(simfilename)]
out_seqs = [item.upper() for item in out_seqs]
out_seqs.sort()
orig_seqs.sort()
# test we see all ground truth sequences and no other
self.assertEqual(out_seqs, orig_seqs)
def validate_results(self, table_name, orig_fasta_name):
res_table = load_table(table_name)
res_seqs = list(res_table.ids(axis='observation'))
exp_seqs = [item[1] for item in sequence_generator(orig_fasta_name)]
exp_seqs = list(map(lambda x: x.upper()[:self.trim_length], exp_seqs))
self.assertListEqual(res_seqs, exp_seqs)
def test_remove_artifacts_from_biom_table(self):
""" Test remove_artifacts_from_biom_table() function for
removing non 16s sequences from a biom table and matching
fasta file. This test uses a pre-calculated biom table and
fasta file and tests the output only 16s and only artifacts
tables
s4 dataset is similar to s2 but with two added non-16s
sequences (which are not phix/adapter)
"""
# create the positive reference databases
pos_ref_fp = join(self.test_data_dir, '70_otus.fasta')
pos_ref_db_fp = build_index_sortmerna(ref_fp=(pos_ref_fp, ),
working_dir=self.working_dir)
# remove the artifacts from the s4 biom table
input_biom_file = join(self.test_data_dir, 'final.s4.biom')
input_fasta_file = join(self.test_data_dir, 'final.s4.seqs.fa')
remove_artifacts_from_biom_table(input_biom_file, input_fasta_file,
[pos_ref_fp], self.working_dir,
pos_ref_db_fp)
origfilename = join(self.test_data_dir, 'simset.s2.fasta')
trim_length = 150
orig_seqs = [item[1] for item in sequence_generator(origfilename)]
orig_seqs = [item[:trim_length].upper() for item in orig_seqs]
no_artifacts_table_name = join(self.working_dir, 'final.only-16s.biom')
no_artifacts_table = load_table(no_artifacts_table_name)
obs_seqs = no_artifacts_table.ids(axis='observation')
self.assertEqual(set(obs_seqs), set(orig_seqs))
artifacts_table_name = join(self.working_dir, 'final.only-non16s.biom')
artifacts_table = load_table(artifacts_table_name)
obs_seqs = artifacts_table.ids(axis='observation')
self.assertEqual(len(obs_seqs), 2)
def test_multiple_sequence_alignment(self):
"""Test multiple sequence alignment.
"""
seqs = [DNA('caccggcggcccggtggtggccattattattgggtctaaag',
metadata={'id': 'seq_1'}, lowercase=True),
DNA('caccggcggcccgagtggtggccattattattgggtcaagg',
metadata={'id': 'seq_2'}, lowercase=True),
DNA('caccggcggcccgagtgatggccattattattgggtctaaag',
metadata={'id': 'seq_3'}, lowercase=True),
DNA('aaccggcggcccaagtggtggccattattattgggtctaaag',
metadata={'id': 'seq_4'}, lowercase=True),
DNA('caccgggcccgagtggtggccattattattgggtctaaag',
metadata={'id': 'seq_5'}, lowercase=True)]
seqs_fp = join(self.working_dir, "seqs.fna")
with open(seqs_fp, 'w') as o:
for seq in seqs:
seq.write(o, format='fasta')
alignment_file = multiple_sequence_alignment(seqs_fp)
aligned_seqs = [DNA(item[1], metadata={'id': item[0]}, lowercase=True)
for item in sequence_generator(alignment_file)]
align_exp = [
DNA('caccggcggcccg-gtggtggccattattattgggtctaaag',
lowercase=True, metadata={'id': 'seq_1'}),
DNA('caccggcggcccgagtggtggccattattattgggtcaagg-',
lowercase=True, metadata={'id': 'seq_2'}),
DNA('caccggcggcccgagtgatggccattattattgggtctaaag',
lowercase=True, metadata={'id': 'seq_3'}),
DNA('aaccggcggcccaagtggtggccattattattgggtctaaag',
lowercase=True, metadata={'id': 'seq_4'}),
DNA('caccg--ggcccgagtggtggccattattattgggtctaaag',
lowercase=True, metadata={'id': 'seq_5'})]
self.assertEqual(aligned_seqs, align_exp)
def get_seqs_act_split_sequence_on_sample_ids(self, output_dir):
"""Parse output of split_sequence_file_on_sample_ids_to_files()
Parameters
----------
output_dir: string
output directory path storing FASTA files
Returns
-------
seqs_act: dict
dictionary with keys being sample IDs and values list of
sequences belonging to sample ID
"""
seqs_act = {}
for fn in listdir(output_dir):
input_fp = join(output_dir, fn)
sample_file = splitext(fn)[0]
for label, seq in sequence_generator(input_fp):
sample = label.split('_')[0]
self.assertEqual(sample_file, sample)
if sample not in seqs_act:
seqs_act[sample] = [(label, seq)]
else:
seqs_act[sample].append((label, seq))
return seqs_act
def test_deblur_indel(self):
"""Test if also removes indel sequences
"""
seqs_f = StringIO(TEST_SEQS_2)
# add the MSA for the indel
seqs = sequence_generator(seqs_f)
newseqs = []
for chead, cseq in seqs:
tseq = cseq[:10] + '-' + cseq[10:]
newseqs.append((chead, tseq))
# now add a sequence with an A insertion
tseq = cseq[:10] + 'A' + cseq[10:-1] + '-'
newseqs.append((chead, tseq))
obs = deblur(newseqs)
# remove the '-' (same as in launch_workflow)
for s in obs:
s.sequence = s.sequence.replace('-', '')
# the expected output
exp = [
Sequence(
"E.Coli-999;size=720;",
"tacggagggtgcaagcgttaatcggaattactgggcgtaaagcgcacgcaggcggt"
"ttgttaagtcagatgtgaaatccccgggctcaacctgggaactgcatctgatactg"
"gcaagcttgagtctcgtagaggggggcagaattccag")
]
# make sure we get 1 sequence as output
self.assertEqual(len(obs), 1)
# and that it is the correct sequence
self.assertEqual(obs[0].sequence, exp[0].sequence)
def test_dereplicate_seqs(self):
""" Test dereplicate_seqs() method functionality,
keep singletons
"""
seqs = [("seq1", "TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAAAGCGTCCG"),
("seq2", "TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAAAGCGTCCG"),
("seq3", "TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAAAGCGTCCG"),
("seq4", "TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAAAGCGTCCT"),
("seq5", "TACCAGCCCCTTAAGTGGTAGGGACGATTATTTGGCCTAAAGCGTCCG"),
("seq6", "CTGCAAGGCTAGGGGGCGGGAGAGGCGGGTGGTACTTGAGGGGAGAAT"),
("seq7", "CTGCAAGGCTAGGGGGCGGGAGAGGCGGGTGGTACTTGAGGGGAGAAT")]
seqs_fp = join(self.working_dir, "seqs.fasta")
with open(seqs_fp, 'w') as seqs_f:
for seq in seqs:
seqs_f.write(">%s\n%s\n" % seq)
output_fp = join(self.working_dir, "seqs_derep.fasta")
dereplicate_seqs(seqs_fp=seqs_fp, output_fp=output_fp, min_size=1)
self.assertTrue(isfile(output_fp))
exp = [("seq1;size=3",
"TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAAAGCGTCCG"),
("seq6;size=2",
"CTGCAAGGCTAGGGGGCGGGAGAGGCGGGTGGTACTTGAGGGGAGAAT"),
("seq4;size=1",
"TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAAAGCGTCCT"),
("seq5;size=1",
"TACCAGCCCCTTAAGTGGTAGGGACGATTATTTGGCCTAAAGCGTCCG")]
act = [item for item in sequence_generator(output_fp)]
self.assertEqual(act, exp)
def run_workflow_try(self, simfilename, origfilename,
ref_fp, ref_db_fp, threads=1,
trim_length=100):
"""Test launching the complete workflow using simulated sequences
and compare to original ground truth.
Parameters
----------
simfilename : str
name of the simulated reads fasta file
origfilename : str
name of the fasta file with the ground truth sequences
ref_fp : list of str
list of the reference database files
def_db_fp : list of str
list of the indexed database files or None to create them
threads : int
number of threads to use (default=1)
trim_length : int
length of sequences to trim to (default=100)
"""
seqs_fp = simfilename
output_fp = self.working_dir
mean_error = 0.005
error_dist = get_default_error_profile()
indel_prob = 0.01
indel_max = 3
min_size = 2
negate = False
nochimera = launch_workflow(seqs_fp=seqs_fp, working_dir=output_fp,
mean_error=mean_error,
error_dist=error_dist,
indel_prob=indel_prob,
indel_max=indel_max,
trim_length=trim_length,
min_size=min_size,
ref_fp=(ref_fp,),
ref_db_fp=ref_db_fp,
negate=negate,
threads_per_sample=threads)
# get the trimmed ground truth sequences
orig_seqs = [item[1] for item in sequence_generator(origfilename)]
orig_seqs = [item[:trim_length].upper() for item in orig_seqs]
output_filename = 'final.biom'
output_table_fp = join(output_fp, output_filename)
create_otu_table(output_table_fp, [(nochimera, seqs_fp)])
table_obs = load_table(output_table_fp)
outseqs = table_obs.ids(axis='observation')
outseqs = list(outseqs)
outseqs.sort()
orig_seqs.sort()
# test we see all ground truth sequences and no other
self.assertEqual(outseqs, orig_seqs)
def test_sequence_generator_invalid_format(self):
allres = []
input_fp = join(self.test_data_dir, 'readme.txt')
msg = "input file %s does not appear to be FASTA or FASTQ" % input_fp
with self.assertWarns(UserWarning) as W:
for res in sequence_generator(input_fp):
allres.append(res)
self.assertEqual(len(allres), 0)
self.assertEqual(str(W.warning), msg)
def test_sequence_generator_fastq(self):
exp_len = 2
first_id = "foo"
first_few_nucs = "GCgc"
obs = list(sequence_generator(self.seqs_fq_fp))
self.assertEqual(len(obs), exp_len)
self.assertEqual(obs[0][0], first_id)
self.assertTrue(obs[0][1].startswith(first_few_nucs))
def test_sequence_generator_fasta(self):
exp_len = 135
first_id = "s1_1001203-10"
first_few_nucs = "TACGTAGGTGGCAAGCGTTA"
obs = list(sequence_generator(self.seqs_s1_fp))
self.assertEqual(len(obs), exp_len)
self.assertEqual(obs[0][0], first_id)
self.assertTrue(obs[0][1].startswith(first_few_nucs))
def test_fasta_from_biom(self):
'''Test the fasta file from biom table function fasta_from_biom()
'''
input_biom_file = join(self.test_data_dir, 'final.s4.biom')
table = load_table(input_biom_file)
output_fasta = join(self.working_dir, 'final.s4.seqs.fa')
fasta_from_biom(table, output_fasta)
self.assertTrue(isfile(output_fasta))
table_seqs = table.ids(axis='observation')
expected = [(seq, seq) for seq in table_seqs]
written_seqs = [item for item in sequence_generator(output_fasta)]
self.assertListEqual(written_seqs, expected)
def test_deblur_toy_example(self):
seqs_f = StringIO(TEST_SEQS_1)
obs = deblur(sequence_generator(seqs_f))
exp = [
Sequence(
"E.Coli;size=1000;",
"tacggagggtgcaagcgttaatcggaattactgggcgtaaagcgcacgcaggcggt"
"ttgttaagtcagatgtgaaatccccgggctcaacctgggaactgcatctgatactg"
"gcaagcttgagtctcgtagaggggggcagaattccag")
]
self.assertEqual(obs, exp)
def test_remove_artifacts_seqs(self):
""" Test remove_artifacts_seqs() function for removing
sequences not matching to a reference database
using SortMeRNA. This test forces a new index
construction for the reference sequences.
"""
seqs = [("seq1", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCC"),
("seq2", "CCTAAAACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("seq3", "TCGCTATTATTGAGCCTAAAACGTCCGTAGTCGGCTTTGTAAATCCC"),
("seq4", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCC"),
("seq5", "CTAAAACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAATAGGGTC"),
("seq6", "TTGAGCCTAAAACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAAT"),
("phix1", "TCTAAAGGTAAAAAACGTTCTGGCGCTCGCCCTGGTCGTCCGCAGCC"),
("phix2", "CTGGCGCTCGCCCTGGTCGTCCGCAGCCGTTGCGAGGTACTAAAGGC"),
("phix3", "GCGCATAAATTTGAGCAGATTTGTCGTCACAGGTTGCGCCGCCAAAA")]
exp_seqs = ["seq1", "seq2", "seq3", "seq4", "seq5", "seq6"]
seqs_fp = join(self.working_dir, "seqs.fasta")
with open(seqs_fp, 'w') as seqs_f:
for seq in seqs:
seqs_f.write(">%s\n%s\n" % seq)
ref = [("ref1", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTA"
"GTCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref2", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref3", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref4", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref5", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATAGGGT"),
("ref6", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT")]
ref_fp = join(self.working_dir, "ref2.fasta")
with open(ref_fp, 'w') as ref_f:
for seq in ref:
ref_f.write(">%s\n%s\n" % seq)
self.files_to_remove.append(ref_fp)
ref_db_fp = build_index_sortmerna(ref_fp=(ref_fp, ),
working_dir=self.working_dir)
output_fp, num_seqs_left, tmp_files = remove_artifacts_seqs(
seqs_fp=seqs_fp,
ref_fp=(ref_fp, ),
working_dir=self.working_dir,
ref_db_fp=ref_db_fp,
negate=False,
threads=1)
obs_seqs = []
for label, seq in sequence_generator(output_fp):
obs_seqs.append(label)
self.assertEqual(obs_seqs, exp_seqs)
# validate it creates one tmp file
self.assertEqual(len(tmp_files), 1)
def test_remove_artifacts_seqs_negate(self):
""" Test remove_artifacts_seqs() function for removing
sequences matching to a reference database
using SortMeRNA.
"""
seqs = [("seq1", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCC"),
("seq2", "CCTAAAACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("seq3", "TCGCTATTATTGAGCCTAAAACGTCCGTAGTCGGCTTTGTAAATCCC"),
("seq4", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCC"),
("seq5", "CTAAAACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAATAGGGTC"),
("seq6", "TTGAGCCTAAAACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAAT"),
("phix1", "TCTAAAGGTAAAAAACGTTCTGGCGCTCGCCCTGGTCGTCCGCAGCC"),
("phix2", "CTGGCGCTCGCCCTGGTCGTCCGCAGCCGTTGCGAGGTACTAAAGGC"),
("phix3", "GCGCATAAATTTGAGCAGATTTGTCGTCACAGGTTGCGCCGCCAAAA")]
# seq5 is 80% similar, so should be kept for 0.95 default similarity
# to artifacts
exp_seqs = ["seq5", "phix1", "phix2", "phix3"]
seqs_fp = join(self.working_dir, "seqs.fasta")
with open(seqs_fp, 'w') as seqs_f:
for seq in seqs:
seqs_f.write(">%s\n%s\n" % seq)
ref = [("ref1", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTA"
"GTCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref2", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref3", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref4", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT"),
("ref5", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATAGGGT"),
("ref6", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAAACGTCCGTAG"
"TCGGCTTTGTAAATCCCTGGGTAAATCGGGT")]
ref_fp = join(self.working_dir, "ref4.fasta")
with open(ref_fp, 'w') as ref_f:
for seq in ref:
ref_f.write(">%s\n%s\n" % seq)
self.files_to_remove.append(ref_fp)
ref_db_fp = build_index_sortmerna([ref_fp], self.working_dir)
output_fp = join(self.working_dir, "seqs_filtered.fasta")
output_fp, num_seqs_left, _ = remove_artifacts_seqs(
seqs_fp=seqs_fp,
ref_fp=(ref_fp, ),
working_dir=self.working_dir,
ref_db_fp=ref_db_fp,
negate=True,
threads=1)
obs_seqs = []
for label, seq in sequence_generator(output_fp):
obs_seqs.append(label)
self.assertEqual(obs_seqs, exp_seqs)
def test_remove_chimeras_denovo_from_seqs(self):
""" Test remove_chimeras_denovo_from_seqs() method functionality.
Remove chimeric sequences from a FASTA file using the UCHIME
algorithm, implemented in VSEARCH.
"""
seqs = [("s1_104;size=2;", "GTGCCAGCCGCCGCGGTAATACCCGCAGCTCAAGTGGTG"
"GTCGCTATTATTGAGCCTAAAACGTCCGTAGTCGGCTTT"
"GTAAATCCCTGGGTAAATCGGGAAGCTTAACTTTCCGAC"
"TTCCGAGGAGACTGTCAAACTTGGGACCGGGAG"),
("s1_106;size=2;", "GTGTCAGCCGCCGCGGTAATACCAGCTCTCCGAGTGGTG"
"TGGATGTTTATTGGGCCTAAAGCGTCCGTAGCCGGCTGC"
"GCAAGTCTGTCGGGAAATCCGCACGCCTAACGTGCGGGC"
"GTCCGGCGGAAACTGCGTGGCTTGGGACCGGAA"),
("s1_1;size=9;", "TACCCGCAGCTCAAGTGGTGGTCGCTATTATTGAGCCTAAA"
"ACGTCCGTAGTCGGCTTTGTAAATCCCTGGGTAAATCGGGT"
"CGCTTAACGATCCGATTCTGGGGAGACTGCAAAGCTTGGGA"
"CCGGGCGAGGTTAGAGGTACTCTCGGG"),
("s1_20;size=9;", "TACCTGCAGCCCAAGTGGTGGTCGATTTTATTGAGTCTAA"
"AACGTTCGTAGCCGGTTTGATAAATCCTTGGGTAAATCGG"
"GAAGCTTAACTTTCCGATTCCGAGGAGACTGTCAAACTTG"
"GGACCGGGAGAGGCTAGAGGTACTTCTGGG"),
("s1_40;size=8;", "TACCAGCTCTCCGAGTGGTGTGGATGTTTATTGGGCCTAA"
"AGCATCCGTAGCTGGCTAGGTTAGTCCCCTGTTAAATCCA"
"CCGAATTAATCGTTGGATGCGGGGGATACTGCTTGGCTAG"
"GGGACGAGAGAGGCAGACGGTATTTCCGGG"),
("s1_60;size=8;", "TACCGGCAGCTCAAGTGATGACCGCTATTATTGGGCCTAA"
"AGCGTCCGTAGCCGGCTGCGCAAGTCTGTCGGGAAATCCG"
"CACGCCTAACGTGCGGGTCCGGCGGAAACTGCGTGGCTTG"
"GGACCGGAAGACTCGAGGGGTACGTCAGGG")]
seqs_non_chimera = [
"s1_1;size=9;", "s1_20;size=9;", "s1_40;size=8;", "s1_60;size=8;"
]
seqs_fp = join(self.working_dir, "seqs.fasta")
with open(seqs_fp, 'w') as seqs_f:
for seq in seqs:
seqs_f.write(">%s\n%s\n" % seq)
output_fp = remove_chimeras_denovo_from_seqs(
seqs_fp=seqs_fp, working_dir=self.working_dir)
seqs_obs = []
for label, seq in sequence_generator(output_fp):
label = label.split()[0]
seqs_obs.append(label)
self.assertEqual(seqs_non_chimera, seqs_obs)
def test_deblur_indel(self):
"""Test if also removes indel sequences
"""
seqs_f = StringIO(TEST_SEQS_2)
# add the MSA for the indel
seqs = sequence_generator(seqs_f)
newseqs = []
for chead, cseq in seqs:
tseq = cseq[:10] + '-' + cseq[10:]
newseqs.append((chead, tseq))
# now add a sequence with an A insertion at the expected freq. (30 < 0.02 * (720 / 0.47) where 0.47 is the mod_factor) so should be removed
cseq = newseqs[0][1]
tseq = cseq[:10] + 'A' + cseq[11:-1] + '-'
chead = '>indel1-read;size=30;'
newseqs.append((chead, tseq))
# and add a sequence with an A insertion but at higher freq. (not expected by indel upper bound - (31 > 0.02 * (720 / 0.47) so should not be removed)
cseq = newseqs[0][1]
tseq = cseq[:10] + 'A' + cseq[11:-1] + '-'
chead = '>indel2-read;size=31;'
newseqs.append((chead, tseq))
obs = deblur(newseqs)
# remove the '-' (same as in launch_workflow)
for s in obs:
s.sequence = s.sequence.replace('-', '')
# the expected output
exp = [
Sequence(
"E.Coli-999;size=720;",
"tacggagggtgcaagcgttaatcggaattactgggcgtaaagcgcacgcaggcggt"
"ttgttaagtcagatgtgaaatccccgggctcaacctgggaactgcatctgatactg"
"gcaagcttgagtctcgtagaggggggcagaattccag")
]
# make sure we get 2 sequences as output - the original and the indel2 (too many reads for the expected indel probabilty)
self.assertEqual(len(obs), 2)
# and that it is the correct sequence
self.assertEqual(obs[0].sequence, exp[0].sequence)
self.assertEqual(obs[1].label, '>indel2-read;size=31;')
def test_create_otu_table(self):
# merge the fasta files
m1 = join(
self.test_data_dir, 'testmerge.fasta.trim.derep.no_artifacts'
'.msa.deblur.no_chimeras')
m2 = join(
self.test_data_dir, 'testmerge2.fasta.trim.derep.no_artifacts'
'.msa.deblur.no_chimeras')
outfile = join(self.working_dir, 'testmerge.biom')
fasta_outfile = join(self.working_dir, 'testmerge.seq.fa')
create_otu_table(outfile, [(m1, 'testmerge'), (m2, 'testmerge2')],
outputfasta_fp=fasta_outfile)
# test the result
table = load_table(outfile)
tableids = table.ids(axis='observation')
# test a sequence present in both
self.assertEqual(
table.get_value_by_ids(
'TACGAGGGGGGCGAGCGTTGTTCGGAATTATTGGGCGTAAAAGGTGCGTAGGCGGTTCG'
'GTAAGTTTCGTGTGAAATCTTCGGGCTCAACTCGAAGCCTGCACGAAATACTGCCGGGC'
'TTGAGTGTGGGAGAGGTGAGTGGAATTTCCGGT', 'testmerge'), 5)
self.assertEqual(
table.get_value_by_ids(
'TACGAGGGGGGCGAGCGTTGTTCG'
'GAATTATTGGGCGTAAAAGGTGCGTAGGCGGTTCGGTAAGTTTCGTGTGAAATCTTCGGG'
'CTCAACTCGAAGCCTGCACGAAATACTGCCGGGCTTGAGTGTGGGAGAGGTGAGTGGAAT'
'TTCCGGT', 'testmerge2'), 8)
# and an otu present only in one
self.assertEqual(
table.get_value_by_ids(
'TACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGAGCGTAGGCGGTTTCTT'
'AAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGGAACTTGA'
'GTGCAGAAGAGGAGAGTGGAATTCCATGT', 'testmerge'), 7)
self.assertEqual(
table.get_value_by_ids(
'TACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGAGCGTAGGCGGTTTCTTA'
'AGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGGAACTTGAGT'
'GCAGAAGAGGAGAGTGGAATTCCATGT', 'testmerge2'), 0)
# test the output fasta file
allseqs = []
for label, seq in sequence_generator(fasta_outfile):
self.assertTrue(seq in tableids)
allseqs.append(seq)
self.assertEqual(len(allseqs), len(tableids))
# test minimal read filtering ( minreads>0 )
minreads = 7
outfile2 = join(self.working_dir, 'testmerge2.biom')
create_otu_table(outfile2, [(m1, 'testmerge'), (m2, 'testmerge2')],
minreads=minreads)
table2 = load_table(outfile2)
table2ids = table2.ids(axis='observation')
tablesum = table.sum(axis='observation')
for idx, cid in enumerate(table.ids(axis='observation')):
if tablesum[idx] >= minreads:
self.assertIn(cid, table2ids)
else:
self.assertNotIn(cid, table2ids)
self.assertEqual(
table2.get_value_by_ids(
'TACGAGGGGGGCGAGCGTTGTTCG'
'GAATTATTGGGCGTAAAAGGTGCGTAGGCGGTTCGGTAAGTTTCGTGTGAAATCTTCGGG'
'CTCAACTCGAAGCCTGCACGAAATACTGCCGGGCTTGAGTGTGGGAGAGGTGAGTGGAAT'
'TTCCGGT', 'testmerge2'), 8)
# and an otu present only in one
self.assertEqual(
table2.get_value_by_ids(
'TACGTAGGTGGCAAGCGTTATCCGGAATTATTGGGCGTAAAGCGAGCGTAGGCGGTTTCTT'
'AAGTCTGATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGGAACTTGA'
'GTGCAGAAGAGGAGAGTGGAATTCCATGT', 'testmerge'), 7)