#!/usr/bin/env python3
# 2025 (c) Micha Johannes Birklbauer
# https://github.com/michabirklbauer/
# micha.birklbauer@gmail.com
from __future__ import annotations
import pandas as pd
from ..data._csm import CrosslinkSpectrumMatch
from ..data._util import check_input
from ..transform._filter import filter_target_decoy
from ..transform._util import check_available_keys
from ._util import __get_filename
from typing import Optional
from typing import List
def __csms_to_xifdr(
csms: List[CrosslinkSpectrumMatch],
filename: Optional[str],
) -> pd.DataFrame:
r"""Exports crosslink-spectrum-matches to xiFDR format.
Parameters
----------
csms : list of CrosslinkSpectrumMatch
A list of crosslink-spectrum-matches.
filename : str, or None
If not None, the data will be written to a file with the specified filename.
Returns
-------
pd.DataFrame
A pandas DataFrame in xiFDR format.
Notes
-----
This function should not be called directly, it is called from ``to_xifdr()``.
"""
run = list()
scan = list()
peptide1 = list()
peptide2 = list()
peptidelink1 = list()
peptidelink2 = list()
isdecoy1 = list()
isdecoy2 = list()
precursorcharge = list()
accession1 = list()
accession2 = list()
peptideposition1 = list()
peptideposition2 = list()
score = list()
for csm in csms:
run.append(csm["spectrum_file"])
scan.append(csm["scan_nr"])
peptide1.append(csm["alpha_peptide"])
peptide2.append(csm["beta_peptide"])
peptidelink1.append(csm["alpha_peptide_crosslink_position"])
peptidelink2.append(csm["beta_peptide_crosslink_position"])
isdecoy1.append("true" if csm["alpha_decoy"] else "false")
isdecoy2.append("true" if csm["beta_decoy"] else "false")
precursorcharge.append(csm["charge"])
accession1.append(";".join(csm["alpha_proteins"]))
accession2.append(";".join(csm["beta_proteins"]))
peptideposition1.append(
";".join([str(pos) for pos in csm["alpha_proteins_peptide_positions"]])
)
peptideposition2.append(
";".join([str(pos) for pos in csm["beta_proteins_peptide_positions"]])
)
score.append(csm["score"])
xifdr_df = pd.DataFrame(
{
"run": run,
"scan": scan,
"peptide1": peptide1,
"peptide2": peptide2,
"peptide link 1": peptidelink1,
"peptide link 2": peptidelink2,
"is decoy 1": isdecoy1,
"is decoy 2": isdecoy2,
"precursor charge": precursorcharge,
"accession1": accession1,
"accession2": accession2,
"peptide position 1": peptideposition1,
"peptide position 2": peptideposition2,
"score": score,
}
)
if filename is not None:
xifdr_df.to_csv(__get_filename(filename, "csv"), index=False)
return xifdr_df
[docs]
def to_xifdr(
csms: List[CrosslinkSpectrumMatch],
filename: Optional[str],
) -> pd.DataFrame:
r"""Exports a list of crosslink-spectrum-matches to xiFDR format.
Exports a list of crosslinks to xiFDR format. The tool xiFDR is accessible
via the link
`rappsilberlab.org/software/xifdr <https://www.rappsilberlab.org/software/xifdr/>`_.
Requires that ``alpha_proteins``, ``beta_proteins``, ``alpha_proteins_peptide_positions``,
``beta_proteins_peptide_positions``, ``alpha_decoy``, ``beta_decoy``, ``charge`` and ``score``
fields are set for all crosslink-spectrum-matches.
Parameters
----------
csms : list of CrosslinkSpectrumMatch
A list of crosslink-spectrum-matches.
filename : str, or None
If not None, the exported data will be written to a file with the specified filename.
Returns
-------
pd.DataFrame
A pandas DataFrame containing crosslink-spectrum-matches in xiFDR format.
Raises
------
TypeError
If a wrong data type is provided.
TypeError
If 'csms' parameter contains elements of mixed data type.
ValueError
If the provided 'csms' parameter contains no elements.
RuntimeError
If not all of the required information is present in the input data.
Examples
--------
>>> from pyXLMS.exporter import to_xifdr
>>> from pyXLMS.parser import read
>>> pr = read(
... "data/ms_annika/XLpeplib_Beveridge_QEx-HFX_DSS_R1_CSMs.xlsx",
... engine="MS Annika",
... crosslinker="DSS",
... )
>>> csms = pr["crosslink-spectrum-matches"]
>>> to_xifdr(csms, filename="msannika_xiFDR.csv")
run scan peptide1 ... peptide position 1 peptide position 2 score
0 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 2257 GQKNSR ... 777 777 119.83
1 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 2448 GQKNSR ... 777 693 13.91
2 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 2561 SDKNR ... 864 864 114.43
3 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 2719 DKQSGK ... 676 676 200.98
4 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 2792 DKQSGK ... 676 45 94.47
.. ... ... ... ... ... ... ...
821 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 23297 MDGTEELLVKLNR ... 387 387 286.05
822 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 23454 KIECFDSVEISGVEDR ... 575 682 376.15
823 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 23581 SSFEKNPIDFLEAK ... 1176 1176 412.44
824 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 23683 SSFEKNPIDFLEAK ... 1176 1176 437.10
825 XLpeplib_Beveridge_QEx-HFX_DSS_R1.raw 27087 MEDESKLHKFKDFK ... 99 1176 15.89
[826 rows x 14 columns]
>>> from pyXLMS.exporter import to_xifdr
>>> from pyXLMS.parser import read
>>> pr = read(
... "data/ms_annika/XLpeplib_Beveridge_QEx-HFX_DSS_R1_CSMs.xlsx",
... engine="MS Annika",
... crosslinker="DSS",
... )
>>> csms = pr["crosslink-spectrum-matches"]
>>> df = to_xifdr(csms, filename=None)
"""
_ok = check_input(csms, "csms", list, CrosslinkSpectrumMatch)
_ok = check_input(filename, "filename", str) if filename is not None else True
if len(csms) == 0:
raise ValueError("Provided crosslink-spectrum-matches contain no elements!")
_ok = check_available_keys(
[
"alpha_proteins",
"beta_proteins",
"alpha_proteins_crosslink_positions",
"beta_proteins_crosslink_positions",
"alpha_decoy",
"beta_decoy",
"charge",
"score",
],
csms,
)
if len(filter_target_decoy(csms)["Target-Decoy"]) == 0:
raise RuntimeError(
"Can't export to xiFDR because number of target-decoy matches is zero!"
)
return __csms_to_xifdr(csms, filename)
