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msfragger_reader.py
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msfragger_reader.py
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import numpy as np
import pandas as pd
from alphabase.psm_reader.psm_reader import (
PSMReaderBase,
psm_reader_yaml,
psm_reader_provider,
)
from alphabase.constants.aa import AA_ASCII_MASS
from alphabase.constants.atom import MASS_H, MASS_O
from alphabase.constants.modification import MOD_MASS
import pyteomics.pepxml as pepxml
def _is_fragger_decoy(proteins):
for prot in proteins:
if not prot.lower().startswith("rev_"):
return False
return True
mass_mapped_mods = psm_reader_yaml["msfragger_pepxml"]["mass_mapped_mods"]
mod_mass_tol = psm_reader_yaml["msfragger_pepxml"]["mod_mass_tol"]
def _get_mods_from_masses(sequence, msf_aa_mods):
mods = []
mod_sites = []
aa_mass_diffs = []
aa_mass_diff_sites = []
for mod in msf_aa_mods:
_mass_str, site_str = mod.split("@")
mod_mass = float(_mass_str)
site = int(site_str)
cterm_position = len(sequence) + 1
if site > 0:
if site < cterm_position:
mod_mass = mod_mass - AA_ASCII_MASS[ord(sequence[site - 1])]
else:
mod_mass -= 2 * MASS_H + MASS_O
else:
mod_mass -= MASS_H
mod_translated = False
for mod_name in mass_mapped_mods:
if abs(mod_mass - MOD_MASS[mod_name]) < mod_mass_tol:
if site == 0:
_mod = mod_name.split("@")[0] + "@Any N-term"
elif site == 1:
if mod_name.endswith("^Any N-term"):
_mod = mod_name
site_str = "0"
else:
_mod = mod_name.split("@")[0] + "@" + sequence[0]
elif site == cterm_position:
if mod_name.endswith("C-term"):
_mod = mod_name
else:
_mod = (
mod_name.split("@")[0] + "@Any C-term"
) # what if only Protein C-term is listed?
site_str = "-1"
else:
_mod = mod_name.split("@")[0] + "@" + sequence[site - 1]
if _mod in MOD_MASS:
mods.append(_mod)
mod_sites.append(site_str)
mod_translated = True
break
if not mod_translated:
aa_mass_diffs.append(f"{mod_mass:.5f}")
aa_mass_diff_sites.append(site_str)
return (
";".join(mods),
";".join(mod_sites),
";".join(aa_mass_diffs),
";".join(aa_mass_diff_sites),
)
class MSFragger_PSM_TSV_Reader(PSMReaderBase):
def __init__(
self,
*,
column_mapping: dict = None,
modification_mapping: dict = None,
fdr=0.01,
keep_decoy=False,
rt_unit="second",
**kwargs,
):
raise NotImplementedError("MSFragger_PSM_TSV_Reader for psm.tsv")
class MSFraggerPepXML(PSMReaderBase):
def __init__(
self,
*,
column_mapping: dict = None,
modification_mapping: dict = None,
fdr=0.001, # refers to E-value in the PepXML
keep_decoy=False,
rt_unit="second",
keep_unknown_aa_mass_diffs=False,
**kwargs,
):
"""MSFragger is not fully supported as we can only access the pepxml file."""
super().__init__(
column_mapping=column_mapping,
modification_mapping=modification_mapping,
fdr=fdr,
keep_decoy=keep_decoy,
rt_unit=rt_unit,
**kwargs,
)
self.keep_unknown_aa_mass_diffs = keep_unknown_aa_mass_diffs
def _init_column_mapping(self):
self.column_mapping = psm_reader_yaml["msfragger_pepxml"]["column_mapping"]
def _init_modification_mapping(self):
self.modification_mapping = {}
def _translate_modifications(self):
pass
def _load_file(self, filename):
msf_df = pepxml.DataFrame(filename)
msf_df.fillna("", inplace=True)
if "ion_mobility" in msf_df.columns:
msf_df["ion_mobility"] = msf_df.ion_mobility.astype(float)
msf_df["raw_name"] = msf_df["spectrum"].str.split(".").apply(lambda x: x[0])
msf_df["to_remove"] = 0
self.column_mapping["to_remove"] = "to_remove"
return msf_df
def _translate_decoy(self, origin_df=None):
self._psm_df["decoy"] = self._psm_df.proteins.apply(_is_fragger_decoy).astype(
np.int8
)
self._psm_df.proteins = self._psm_df.proteins.apply(lambda x: ";".join(x))
if not self.keep_decoy:
self._psm_df["to_remove"] += self._psm_df.decoy > 0
def _translate_score(self, origin_df=None):
# evalue score
self._psm_df["score"] = -np.log(self._psm_df["score"] + 1e-100)
def _load_modifications(self, msf_df):
if len(msf_df) == 0:
self._psm_df["mods"] = ""
self._psm_df["mod_sites"] = ""
self._psm_df["aa_mass_diffs"] = ""
self._psm_df["aa_mass_diff_sites"] = ""
return
(
self._psm_df["mods"],
self._psm_df["mod_sites"],
self._psm_df["aa_mass_diffs"],
self._psm_df["aa_mass_diff_sites"],
) = zip(
*msf_df[["peptide", "modifications"]].apply(
lambda x: _get_mods_from_masses(*x), axis=1
)
)
if not self.keep_unknown_aa_mass_diffs:
self._psm_df["to_remove"] += self._psm_df.aa_mass_diffs != ""
self._psm_df.drop(
columns=["aa_mass_diffs", "aa_mass_diff_sites"], inplace=True
)
def _post_process(self, origin_df: pd.DataFrame):
super()._post_process(origin_df)
self._psm_df = (
self._psm_df.query("to_remove==0")
.drop(columns="to_remove")
.reset_index(drop=True)
)
def register_readers():
psm_reader_provider.register_reader("msfragger_psm_tsv", MSFragger_PSM_TSV_Reader)
psm_reader_provider.register_reader("msfragger", MSFragger_PSM_TSV_Reader)
psm_reader_provider.register_reader("msfragger_pepxml", MSFraggerPepXML)