def test_annotate_peptide_fragments():
fragment_tol_mass = 0.02
fragment_tol_mode = 'Da'
peptides = [
'SYELPDGQVITIGNER', 'MFLSFPTTK', 'DLYANTVLSGGTTMYPGIADR', 'YLYEIAR',
'VAPEEHPVLLTEAPLNPK'
]
for peptide in peptides:
fragment_mz = np.asarray([
fragment.calc_mz for fragment in
spectrum._get_theoretical_peptide_fragments(peptide)
])
fragment_mz += np.random.uniform(-0.9 * fragment_tol_mass,
0.9 * fragment_tol_mass,
len(fragment_mz))
num_peaks = 150
mz = np.random.uniform(100, 1400, num_peaks)
mz[:len(fragment_mz)] = fragment_mz
intensity = np.random.lognormal(0, 1, num_peaks)
charge = 2
spec = spectrum.MsmsSpectrum('test_spectrum',
mass.calculate_mass(sequence=peptide,
charge=charge),
charge,
mz,
intensity,
peptide=peptide)
spec.annotate_peptide_fragments(fragment_tol_mass, fragment_tol_mode)
assert np.count_nonzero(spec.annotation) == len(fragment_mz)
def test_get_theoretical_fragments_mod_multiple():
peptide = 'HPYLEDR'
modifications = {'N-term': 42.01056, 2: 79.96633}
fragments = {'b1': 180.076706, 'b2': 277.129486, 'b3': 520.159180,
'b4': 633.243225, 'b5': 762.285828, 'b6': 877.312744,
'y1': 175.118912, 'y2': 290.145844, 'y3': 419.188446,
'y4': 532.272522, 'y5': 775.302185, 'y6': 872.354980}
for fragment in spectrum._get_theoretical_peptide_fragments(
peptide, modifications):
fragment_mz = fragments[f'{fragment.ion_type}{fragment.ion_index}']
assert fragment.calc_mz == pytest.approx(fragment_mz)
def test_get_theoretical_fragments_mod_term():
peptide = 'HPYLEDR'
modifications = {'N-term': 42.01056}
fragments = {'b1': 180.076706, 'b2': 277.129486, 'b3': 440.192810,
'b4': 553.276917, 'b5': 682.319519, 'b6': 797.346436,
'y1': 175.118912, 'y2': 290.145844, 'y3': 419.188446,
'y4': 532.272522, 'y5': 695.335815, 'y6': 792.388550}
for fragment in spectrum._get_theoretical_peptide_fragments(
peptide, modifications):
fragment_mz = fragments[f'{fragment.ion_type}{fragment.ion_index}']
assert fragment.calc_mz == pytest.approx(fragment_mz)
def test_get_theoretical_fragments_static_mod():
spectrum.static_modification('Y', 79.96633)
peptide = 'HPYLEDR'
fragments = {
'b1_1': 138.066147,
'b2_1': 235.118912,
'b3_1': 478.148590,
'b4_1': 591.232666,
'b5_1': 720.275269,
'b6_1': 835.302185,
'y1_1': 175.118912,
'y2_1': 290.145844,
'y3_1': 419.188446,
'y4_1': 532.272522,
'y5_1': 775.302185,
'y6_1': 872.354980,
'b1_2': 69.536731,
'b2_2': 118.063111,
'b3_2': 239.577941,
'b4_2': 296.119971,
'b5_2': 360.641266,
'b6_2': 418.154736,
'y1_2': 88.063114,
'y2_2': 145.576584,
'y3_2': 210.097879,
'y4_2': 266.639909,
'y5_2': 388.154739,
'y6_2': 436.681119,
'b1_3': 46.693580,
'b2_3': 79.044500,
'b3_3': 160.054386,
'b4_3': 197.749073,
'b5_3': 240.763270,
'b6_3': 279.105583,
'y1_3': 59.044501,
'y2_3': 97.386815,
'y3_3': 140.401011,
'y4_3': 178.095698,
'y5_3': 259.105585,
'y6_3': 291.456505
}
for fragment in spectrum._get_theoretical_peptide_fragments(peptide,
None,
max_charge=3):
fragment_mz = fragments[f'{fragment.ion_type}{fragment.ion_index}'
f'_{fragment.charge}']
assert fragment.calc_mz == pytest.approx(fragment_mz)
assert spectrum._aa_mass['Y'] == pytest.approx(163.06333 + 79.96633)
spectrum.reset_modifications()
assert spectrum._aa_mass['Y'] == pytest.approx(163.06333)
def plot_spectrum(identifier, precursor_mz, precursor_charge, mz, intensity,
retention_time, peptide):
# identifier = spectrum_dict['params']['title']
# precursor_mz = spectrum_dict['params']['pepmass'][0]
# precursor_charge = spectrum_dict['params']['charge'][0]
# mz = spectrum_dict['m/z array']
# intensity = spectrum_dict['intensity array']
# retention_time = float(spectrum_dict['params']['rtinseconds'])
# peptide = 'WNQLQAFWGTGK'
# Create the MS/MS spectrum.
spectrum = sus.MsmsSpectrum(identifier,
precursor_mz=precursor_mz,
precursor_charge=precursor_charge,
mz=mz,
intensity=intensity,
retention_time=retention_time,
peptide=peptide)
# Process the MS/MS spectrum.
# fragment_tol_mass = 10
# fragment_tol_mode = 'ppm'
fragment_tol_mass = .5
fragment_tol_mode = 'Da'
spectrum = (spectrum.set_mz_range(
min_mz=100, max_mz=1400).remove_precursor_peak(
fragment_tol_mass, fragment_tol_mode).filter_intensity(
min_intensity=0.05, max_num_peaks=50).scale_intensity(
'root').annotate_peptide_fragments(fragment_tol_mass,
fragment_tol_mode,
ion_types='aby'))
# Generate theoretical spec
ts = sus._get_theoretical_peptide_fragments(peptide)
tmz = [frag.calc_mz for frag in ts]
ti = [1.0 for _ in tmz]
tspec = sus.MsmsSpectrum(identifier,
precursor_mz=precursor_mz,
precursor_charge=precursor_charge,
mz=tmz,
intensity=ti,
retention_time=retention_time,
peptide=peptide)
# Plot the MS/MS spectrum.
fig, ax = plt.subplots(figsize=(12, 6))
# sup.spectrum(spectrum, ax=ax)
sup.mirror(spectrum, tspec, ax=ax)
plt.show()
plt.close()
def test_get_theoretical_fragments():
peptide = 'HPYLEDR'
fragments = {
'b1_1': 138.066147,
'b2_1': 235.118912,
'b3_1': 398.182220,
'b4_1': 511.266266,
'b5_1': 640.308899,
'b6_1': 755.335815,
'y1_1': 175.118912,
'y2_1': 290.145844,
'y3_1': 419.188446,
'y4_1': 532.272522,
'y5_1': 695.335815,
'y6_1': 792.388550,
'b1_2': 69.536731,
'b2_2': 118.063111,
'b3_2': 199.594776,
'b4_2': 256.136806,
'b5_2': 320.658101,
'b6_2': 378.171571,
'y1_2': 88.063114,
'y2_2': 145.576584,
'y3_2': 210.097879,
'y4_2': 266.639909,
'y5_2': 348.171574,
'y6_2': 396.697954,
'b1_3': 46.693580,
'b2_3': 79.044500,
'b3_3': 133.398943,
'b4_3': 171.093630,
'b5_3': 214.107826,
'b6_3': 252.450140,
'y1_3': 59.044501,
'y2_3': 97.386815,
'y3_3': 140.401011,
'y4_3': 178.095698,
'y5_3': 232.450141,
'y6_3': 264.801061
}
for fragment in spectrum._get_theoretical_peptide_fragments(peptide,
max_charge=3):
fragment_mz = fragments[f'{fragment.ion_type}{fragment.ion_index}'
f'_{fragment.charge}']
assert fragment.calc_mz == pytest.approx(fragment_mz)
def test_annotate_peaks_most_intense():
fragment_tol_mass = 0.02
fragment_tol_mode = 'Da'
peptide = 'YLYEIAR'
fragment_mz = np.asarray([mz for _, mz in
spectrum._get_theoretical_peptide_fragments(
peptide)])
mz = np.asarray([fragment_mz[0] - 0.01, fragment_mz[0] + 0.01])
intensity = np.asarray([10, 20])
charge = 2
spec = spectrum.MsmsSpectrum(
'test_spectrum', mass.calculate_mass(sequence=peptide,
charge=charge),
charge, mz, intensity, peptide=peptide)
spec.annotate_peaks(fragment_tol_mass, fragment_tol_mode,
peak_assignment='most_intense')
assert spec.annotation[0] is None
assert spec.annotation[1] is not None
def test_annotate_peaks_nearest_mz():
fragment_tol_mass = 0.02
fragment_tol_mode = 'Da'
peptide = 'YLYEIAR'
fragment_mz = np.asarray([fragment.calc_mz for fragment in
spectrum._get_theoretical_peptide_fragments(
peptide)])
mz = np.asarray([fragment_mz[0] - 0.005, fragment_mz[0] + 0.015])
intensity = np.asarray([10, 20])
charge = 2
spec = spectrum.MsmsSpectrum(
'test_spectrum', mass.calculate_mass(sequence=peptide,
charge=charge),
charge, mz, intensity, peptide=peptide)
spec.annotate_peaks(fragment_tol_mass, fragment_tol_mode,
peak_assignment='nearest_mz')
assert spec.annotation[0] == spectrum.FragmentAnnotation('b', 1, 1,
fragment_mz[0])
assert spec.annotation[1] is None
def _get_theoretical_fragment_mzs(sequence: str) -> np.ndarray:
"""
Get the theoretical b and y ion m/z values for the given peptide sequence.
Parameters
----------
sequence : str
The peptide sequence for which b and y ion m/z values will be
calculated.
Returns
-------
np.ndarray
An array of sorted m/z values of the b and y ions for the given peptide
sequence.
"""
# Correct for 0-based offsets required by spectrum_utils.
mods, mod_pos_offset = {}, 1
for match in re.finditer(regex_mod, sequence):
mods[match.start() - mod_pos_offset] = float(match.group(0))
mod_pos_offset += match.end() - match.start()
return np.asarray([fragment.calc_mz for fragment in
sus._get_theoretical_peptide_fragments(
_remove_mod(sequence), mods)])
