Source code for pyXLMS.exporter._to_impxfdr
#!/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._crosslink import Crosslink
from ..data._csm import create_crosslink_from_csm
from ..data._util import check_input
from ..transform._util import check_available_keys
from ..transform._util import assert_csms
from ..transform._util import assert_xls
from ..transform._util import assert_csms_or_xls
from ..transform._filter import filter_target_decoy
from ._to_msannika import to_msannika
from typing import Optional
from typing import List
[docs]
def to_impxfdr(
data: List[CrosslinkSpectrumMatch] | List[Crosslink],
filename: Optional[str],
targets_only: bool = True,
) -> pd.DataFrame:
r"""Exports a list of crosslinks or crosslink-spectrum-matches to IMP-X-FDR format.
Exports a list of crosslinks or crosslink-spectrum-matches to IMP-X-FDR format for benchmarking purposes.
The tool IMP-X-FDR is available from
`github.com/vbc-proteomics-org/imp-x-fdr <https://github.com/vbc-proteomics-org/imp-x-fdr>`_.
We recommend using version 1.1.0 and selecting "MS Annika" as input file format for the here exported file.
A slightly modified version is available from
`github.com/hgb-bin-proteomics/MSAnnika_NC_Results <https://github.com/hgb-bin-proteomics/MSAnnika_NC_Results/blob/master/Peplib_Beveridge/MS_Annika/Tools/IMP-X-FDR.v1.1.0.zip>`_.
This version contains a few bug fixes and was used for the MS Annika 2.0 and MS Annika 3.0 publications.
Requires that ``alpha_proteins``, ``beta_proteins``, ``alpha_proteins_crosslink_positions`` and ``beta_proteins_crosslink_positions`` fields
are set for crosslinks and crosslink-spectrum-matches.
Parameters
----------
data : list of CrosslinkSpectrumMatch, or list of Crosslink
A list of crosslinks or crosslink-spectrum-matches.
filename : str, or None, default = None
If not None, the exported data will be written to a file with the specified filename.
The filename should end in ".xlsx" as the file is exported to Microsoft Excel file format.
targets_only : bool, default = True
Whether or not only target crosslinks or crosslink-spectrum-matches should be exported. For
benchmarking purposes this is usually the case. If the crosslinks or crosslink-spectrum-matches
do not contain target-decoy labels this should be set to False.
Returns
-------
pd.DataFrame
A pandas DataFrame containing crosslinks or crosslink-spectrum-matches in IMP-X-FDR format.
Raises
------
TypeError
If a wrong data type is provided.
TypeError
If data contains elements of mixed data type.
ValueError
If the provided data contains no elements or if none of the data has target-decoy labels
and parameter 'targets_only' is set to True.
RuntimeError
If not all of the required information is present in the input data.
Examples
--------
>>> from pyXLMS.exporter import to_impxfdr
>>> from pyXLMS.parser import read
>>> pr = read(
... "data/xi/1perc_xl_boost_Links_xiFDR2.2.1.csv",
... engine="xiSearch/xiFDR",
... crosslinker="DSS",
... )
>>> crosslinks = pr["crosslinks"]
>>> to_impxfdr(crosslinks, filename="crosslinks.xlsx")
Crosslink Type Sequence A Position A Accession A In protein A ... Position B Accession B In protein B Best CSM Score Decoy
0 Intra VVDELV[K]VMGR 7 Cas9 753 ... 7 Cas9 753 40.679 False
1 Intra MLASAGELQ[K]GNELALPSK 10 Cas9 753 ... 7 Cas9 1226 40.231 False
2 Intra MDGTEELLV[K]LNR 10 Cas9 396 ... 10 Cas9 396 39.582 False
3 Intra MTNFD[K]NLPNEK 6 Cas9 965 ... 2 Cas9 504 35.880 False
4 Intra DFQFY[K]VR 6 Cas9 978 ... 4 Cas9 1028 35.281 False
.. ... ... ... ... ... ... ... ... ... ... ...
220 Intra LP[K]YSLFELENGR 3 Cas9 866 ... 3 Cas9 1204 9.877 False
221 Intra D[K]QSGK 2 Cas9 677 ... 2 Cas9 677 9.702 False
222 Intra AGFI[K]R 5 Cas9 922 ... 11 Cas9 881 9.666 False
223 Intra E[K]IEK 2 Cas9 443 ... 1 Cas9 562 9.656 False
224 Intra LS[K]SR 3 Cas9 222 ... 3 Cas9 222 9.619 False
[225 rows x 11 columns]
>>> from pyXLMS.exporter import to_impxfdr
>>> from pyXLMS.parser import read
>>> pr = read(
... "data/xi/1perc_xl_boost_CSM_xiFDR2.2.1.csv",
... engine="xiSearch/xiFDR",
... crosslinker="DSS",
... )
>>> csms = pr["crosslink-spectrum-matches"]
>>> to_impxfdr(csms, filename="csms.xlsx")
Crosslink Type Sequence A Position A Accession A In protein A ... Position B Accession B In protein B Best CSM Score Decoy
0 Intra [K]IECFDSVEISGVEDR 1 Cas9 575 ... 1 Cas9 575 27.268 False
1 Intra LVDSTD[K]ADLR 7 Cas9 152 ... 11 Cas9 881 26.437 False
2 Intra GGLSELD[K]AGFIK 8 Cas9 917 ... 8 Cas9 917 26.134 False
3 Intra LVDSTD[K]ADLR 7 Cas9 152 ... 7 Cas9 152 25.804 False
4 Intra VVDELV[K]VMGR 7 Cas9 753 ... 7 Cas9 753 24.861 False
.. ... ... ... ... ... ... ... ... ... ... ...
406 Intra [K]GILQTVK 1 Cas9 739 ... 3 Cas9 222 6.977 False
407 Intra QQLPE[K]YK 6 Cas9 350 ... 6 Cas9 350 6.919 False
408 Intra ESILP[K]R 6 Cas9 1117 ... 7 Cas9 1035 6.853 False
409 Intra LS[K]SR 3 Cas9 222 ... 2 Cas9 884 6.809 False
410 Intra QIT[K]HVAQILDSR 4 Cas9 933 ... 6 Cas9 350 6.808 False
[411 rows x 11 columns]
"""
_ok = check_input(data, "data", list)
_ok = check_input(filename, "filename", str) if filename is not None else True
_ok = check_input(targets_only, "targets_only", bool)
data = assert_csms_or_xls(data)
if targets_only:
data = filter_target_decoy(data)["Target-Target"]
if len(data) == 0:
if targets_only:
raise ValueError(
"Provided data does not contain any crosslinks or crosslink-spectrum-matches after filtering for targets only!"
)
else:
raise ValueError(
"Provided data does not contain any crosslinks or crosslink-spectrum-matches!"
)
_ok = check_available_keys(
[
"alpha_proteins",
"alpha_proteins_crosslink_positions",
"beta_proteins",
"beta_proteins_crosslink_positions",
],
data,
)
if isinstance(data[0], Crosslink):
return to_msannika(assert_xls(data), filename, format="xlsx")
return to_msannika(
[create_crosslink_from_csm(csm) for csm in assert_csms(data)],
filename,
format="xlsx",
)
