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iRT,
aMass,
precursor_charge,
sequence_integer,
aIons,
):
self.aIntensity = aIntensity
self.collision_energy = collision_energy
self.iRT = iRT
self.aMass = aMass
self.precursor_charge = precursor_charge
self.aIons = aIons
self.mod, self.mod_string = generate_mod_strings(sequence_integer)
self.sequence = utils.get_sequence(sequence_integer)
# amino acid Z which is defined at the toplevel in generate_aa_comp
self.precursor_mass = pyteomics.mass.calculate_mass(
self.sequence.replace("M(ox)", "Z"),
aa_comp=aa_comp,
ion_type="M",
charge=int(self.precursor_charge),
)
def prot_to_peprec(protein):
params = get_params()
# Calculate longest and shortest possible peptide with given max_pepmass
max_pepmass_min_len = int(params['max_pepmass'] / 186.08 + 2)
max_pepmass_max_len = int(params['max_pepmass'] / 57.02 + 2)
tmp = pd.DataFrame(columns=['spec_id', 'peptide', 'modifications', 'charge'])
pep_count = 0
for peptide in cleave(str(protein.seq), expasy_rules['trypsin'], params['missed_cleavages']):
if False not in [aa not in peptide for aa in ['B', 'J', 'O', 'U', 'X', 'Z']]:
if params['min_peplen'] <= len(peptide) <= max_pepmass_max_len:
# Skip peptide if it's mass is larger than allowed
# Only calculate if longer than shortest possible peptide with max_pepmass
if len(peptide) > max_pepmass_min_len:
if mass.calculate_mass(sequence=peptide) > params['max_pepmass']:
continue
pep_count += 1
row = {
'spec_id': '{}_{:03d}'.format(protein.id, pep_count),
'peptide': peptide, 'modifications': '-', 'charge': np.nan
}
tmp = tmp.append(row, ignore_index=True)
return tmp