def test_conversion(chars_per_line):
path = os.path.join(data_dir("sequence"), "random.fastq")
fasta_file = fastq.FastqFile.read(
path, offset=33, chars_per_line=chars_per_line
)
ref_content = dict(fasta_file.items())
fasta_file = fastq.FastqFile(offset=33, chars_per_line=chars_per_line)
for identifier, (sequence, scores) in ref_content.items():
fasta_file[identifier] = sequence, scores
temp = TemporaryFile("w+")
fasta_file.write(temp)
temp.seek(0)
fasta_file = fastq.FastqFile.read(
temp, offset=33, chars_per_line=chars_per_line
)
content = dict(fasta_file.items())
temp.close()
for identifier in ref_content:
ref_sequence, ref_scores = ref_content[identifier]
test_sequence, test_scores = content[identifier]
assert test_sequence == ref_sequence
assert np.array_equal(test_scores, ref_scores)
def test_rna_conversion():
sequence = seq.NucleotideSequence("ACGT")
scores = np.array([0, 0, 0, 0])
fastq_file = fastq.FastqFile(offset="Sanger")
fastq.set_sequence(fastq_file, sequence, scores, "seq1", as_rna=False)
fastq.set_sequence(fastq_file, sequence, scores, "seq2", as_rna=True)
assert fastq_file["seq1"][0] == "ACGT"
assert fastq_file["seq2"][0] == "ACGU"
def test_conversion(chars_per_line):
path = os.path.join(data_dir, "random.fastq")
file1 = fastq.FastqFile(offset=33, chars_per_line=chars_per_line)
file1.read(path)
ref_content = dict(file1.items())
file2 = fastq.FastqFile(offset=33, chars_per_line=chars_per_line)
for identifier, (sequence, scores) in ref_content.items():
file2[identifier] = sequence, scores
file2.write(biotite.temp_file("fastq"))
file3 = fastq.FastqFile(offset=33, chars_per_line=chars_per_line)
file3.read(path)
content = dict(file3.items())
for identifier in ref_content:
ref_sequence, ref_scores = ref_content[identifier]
sequence, scores = content[identifier]
assert ref_sequence == sequence
assert np.array_equal(ref_scores, scores)
def test_write_iter(offset, chars_per_line, n_sequences):
"""
Test whether :class:`FastqFile.write()` and
:class:`FastqFile.write_iter()` produce the same output file for
random sequences and scores.
"""
LENGTH_RANGE = (50, 150)
SCORE_RANGE = (10, 60)
# Generate random sequences and scores
np.random.seed(0)
sequences = []
scores = []
for i in range(n_sequences):
seq_length = np.random.randint(*LENGTH_RANGE)
code = np.random.randint(
len(seq.NucleotideSequence.alphabet_unamb),
size=seq_length
)
sequence = seq.NucleotideSequence()
sequence.code = code
sequences.append(sequence)
score = np.random.randint(*SCORE_RANGE, size=seq_length)
scores.append(score)
fastq_file = fastq.FastqFile(offset, chars_per_line)
for i, (sequence, score) in enumerate(zip(sequences, scores)):
identifier = f"seq_{i}"
fastq_file[identifier] = (str(sequence), score)
ref_file = io.StringIO()
fastq_file.write(ref_file)
test_file = io.StringIO()
fastq.FastqFile.write_iter(
test_file,
(
(f"seq_{i}", (str(sequence), score))
for i, (sequence, score) in enumerate(zip(sequences, scores))
),
offset, chars_per_line
)
assert test_file.getvalue() == ref_file.getvalue()
def test_access(chars_per_line):
path = os.path.join(data_dir, "random.fastq")
file = fastq.FastqFile(offset=33, chars_per_line=chars_per_line)
file.read(path)
assert len(file) == 20
assert list(file.keys()) == [f"Read:{i+1:02d}" for i in range(20)]
del (file["Read:05"])
assert len(file) == 19
assert list(
file.keys()) == [f"Read:{i+1:02d}" for i in range(20) if i + 1 != 5]
for sequence, scores in file.values():
assert len(sequence) == len(scores)
assert (scores >= 0).all()
sequence = seq.NucleotideSequence("ACTCGGT")
scores = np.array([10, 12, 20, 11, 0, 80, 42])
file["test"] = sequence, scores
sequence2, scores2 = file["test"]
assert sequence == sequence2
assert np.array_equal(scores, scores2)
from io import StringIO
import numpy as np
import matplotlib.pyplot as plt
import biotite
import biotite.sequence as seq
import biotite.sequence.io.fastq as fastq
# Sample FASTQ file from https://en.wikipedia.org/wiki/FASTQ_format
fastq_content = StringIO("""
@SEQ_ID
GATTTGGGGTTCAAAGCAGTATCGATCAAATAGTAAATCCATTTGTTCAACTCACAGTTT
+
!''*((((***+))%%%++)(%%%%).1***-+*''))**55CCF>>>>>>CCCCCCC65
""")
fastq_file = fastq.FastqFile(offset="Sanger")
fastq_file.read(fastq_content)
sequence = fastq_file.get_sequence("SEQ_ID")
scores = fastq_file.get_quality("SEQ_ID")
figure, ax = plt.subplots(figsize=(8.0, 2.0))
ax.bar(x=np.arange(len(sequence)),
height=scores,
color=biotite.colors["orange"],
width=1.0,
linewidth=1,
edgecolor="white")
# -1 to put space between Y-axis and sequence
ax.set_xlim(-1, len(sequence))
# The range of Phred scores
ax.set_ylim(0, 40)