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writer.py
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writer.py
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from dataclasses import dataclass
from data_reader import DDAFeature
import config
import logging
import numpy as np
logger = logging.getLogger(__name__)
@dataclass
class BeamSearchedSequence:
sequence: list # list of aa id
position_score: list
score: float # average by length score
class DenovoWriter(object):
def __init__(self, denovo_output_file):
self.output_handle = open(denovo_output_file, 'w')
header_list = ["feature_id",
"feature_area",
"predicted_sequence",
"predicted_score",
"predicted_position_score",
"precursor_mz",
"precursor_charge",
"protein_access_id",
"scan_list_middle",
"scan_list_original",
"predicted_score_max"]
header_row = "\t".join(header_list)
print(header_row, file=self.output_handle, end='\n')
def close(self):
self.output_handle.close()
def write(self, dda_original_feature: DDAFeature, searched_sequence: BeamSearchedSequence):
"""
keep the output in the same format with the tensorflow version
:param dda_original_feature:
:param searched_sequence:
:return:
"""
feature_id = dda_original_feature.feature_id
feature_area = dda_original_feature.feature_area
precursor_mz = str(dda_original_feature.mz)
precursor_charge = str(dda_original_feature.z)
scan_list_middle = dda_original_feature.scan
scan_list_original = dda_original_feature.scan
if searched_sequence.sequence:
predicted_sequence = ','.join([config.vocab_reverse[aa_id] for
aa_id in searched_sequence.sequence])
predicted_score = "{:.2f}".format(searched_sequence.score)
predicted_score_max = predicted_score
predicted_position_score = ','.join(['{0:.2f}'.format(x) for x in searched_sequence.position_score])
protein_access_id = 'DENOVO'
else:
predicted_sequence = ""
predicted_score = ""
predicted_score_max = ""
predicted_position_score = ""
protein_access_id = ""
predicted_row = "\t".join([feature_id,
feature_area,
predicted_sequence,
predicted_score,
predicted_position_score,
precursor_mz,
precursor_charge,
protein_access_id,
scan_list_middle,
scan_list_original,
predicted_score_max])
print(predicted_row, file=self.output_handle, end="\n")
def __del__(self):
self.close()
@dataclass
class PSM:
feature_id: str
scan: str
num_id: int
exp_mass: float
calc_mass: float
charge: int
peptide_str: str
accession_id: str
is_decoy: bool
length_score: float
log_length_score: float
length_normalized_score: float
log_length_normalized_score: float
ppm: float
peptide_length: int
num_var_mod: int
class PercolatorWriter(object):
def __init__(self, denovo_output_file):
self.output_handle = open(denovo_output_file, 'w')
header_list = ["FeatureID", # 0
"Label", # 1
"ScanNr", # 2
"ExpMass", # 3
"CalcMass", # 4
"LengthScore", # 5
"LengthNormalizedScore", # 6
"LogLengthScore", # 7
"LogLengthNormalizedScore", # 8
"PpmAbsDiff", # 9
"PepLen", # 10
"Charge1", # 11
"Charge2", # 12
"Charge3", # 13
"Charge4", # 14
"Charge5", # 15
"Charge6", # 16
"NumVarMod", # 17
"Peptide", # 18
"Proteins", # 19
]
header_row = "\t".join(header_list)
print(header_row, file=self.output_handle, end='\n')
self.scan_nr_counter = 1
def close(self):
self.output_handle.close()
def write(self, psm: PSM):
feature_id = psm.feature_id + '_' + str(psm.num_id)
if psm.is_decoy:
label = '-1'
else:
label= '1'
# label = str(psm.is_decoy is False)
scan_nr = f"{self.scan_nr_counter}"
self.scan_nr_counter += 1
exp_mass = "{:.4f}".format(psm.exp_mass)
calc_mass = "{:.4f}".format(psm.calc_mass)
length_score = "{:.4f}".format(psm.length_score)
length_normalized_score = "{:.4f}".format(psm.length_normalized_score)
log_length_score = "{:.4f}".format(psm.log_length_score)
log_length_normalized_score = "{:.4f}".format(psm.log_length_normalized_score)
ppm = "{:.4f}".format(np.abs(psm.ppm))
pep_len = str(psm.peptide_length)
print_list = [feature_id,
label,
scan_nr,
exp_mass,
calc_mass,
length_score,
length_normalized_score,
log_length_score,
log_length_normalized_score,
ppm,
pep_len]
charge = ["0"] * 6
charge_index = min(psm.charge - 1, 5)
charge[charge_index] = "1"
print_list += charge
print_list.append(str(psm.num_var_mod))
print_list.append(psm.peptide_str)
print_list.append(psm.accession_id)
print("\t".join(print_list), file=self.output_handle, end="\n")