Report generation fails with "IndexError: single positional indexer is out-of-bounds" #231
Description
Hi,
I'm encountering an error when running MS²Rescore with the following config:
{
"$schema": "./config_schema.json",
"ms2rescore": {
"feature_generators": {
"basic": {},
"ms2pip": {
"model": "HCD",
"ms2_tolerance": 0.02
},
"deeplc": {
"calibration_set_size": 0.4
}
},
"rescoring_engine": {
"percolator": {}
},
"psm_file": null,
"psm_file_type": "xtandem",
"psm_reader_kwargs": {},
"spectrum_path": null,
"output_path": null,
"log_level": "info",
"id_decoy_pattern": "decoy_",
"psm_id_pattern": "([a-fA-F0-9]{8}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{12})",
"spectrum_id_pattern": "([a-fA-F0-9]{8}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{4}-[a-fA-F0-9]{12})",
"lower_score_is_better": false,
"modification_mapping": {
"+57.022": "U:Carbamidomethyl",
"+15.994": "U:Oxidation",
"+39.9954": "U:Pyro-carbamidomethyl",
"+42.0106": "U:Acetyl",
"-17.0266": "U:Gln->pyro-Glu",
"-18.0106": "U:Glu->pyro-Glu"
},
"fixed_modifications": {},
"processes": -1,
"rename_to_usi": false,
"fasta_file": null,
"write_report": true
}
}
Everything seems to work fine up to the rescoring step, but when generating the final report, the process fails with the following error:
2025-07-14 15:21:49 INFO ms2rescore.feature_generators.deeplc // Adding
DeepLC-derived features to PSMs.
INFO ms2rescore.feature_generators.deeplc // Running
DeepLC for PSMs from run (1/1): spectra...
2025-07-14 15:22:11 INFO ms2rescore.rescoring_engines.percolator //
Percolator output:
Protein decoy-prefix used is decoy_
All files have been read
Percolator version 3.06.1, Build Date Jun 15 2023
14:55:20
Copyright (c) 2006-9 University of Washington. All
rights reserved.
Written by Lukas Käll ([email protected]) in
the
Department of Genome Sciences at the University of
Washington.
Issued command:
percolator --results-psms
/xtandemserver/download/output2.ms2rescore.percolat
or.psms.pout --decoy-results-psms
/xtandemserver/download/output2.ms2rescore.percolat
or.decoy.psms.pout --results-peptides
/xtandemserver/download/output2.ms2rescore.percolat
or.peptides.pout --decoy-results-peptides
/xtandemserver/download/output2.ms2rescore.percolat
or.decoy.peptides.pout --results-proteins
/xtandemserver/download/output2.ms2rescore.percolat
or.proteins.pout --decoy-results-proteins
/xtandemserver/download/output2.ms2rescore.percolat
or.decoy.proteins.pout --weights
/xtandemserver/download/output2.ms2rescore.percolat
or.weights.tsv --verbose 1 --num-threads 8
--post-processing-tdc
/xtandemserver/download/output2.ms2rescore.pin
Started Mon Jul 14 15:21:57 2025
on xtandem-6b9f78b46b-l5nxm
Hyperparameters: selectionFdr=0.01, Cpos=0, Cneg=0,
maxNiter=10
Concatenated search input detected and
--post-processing-tdc flag set. Applying
target-decoy competition on Percolator scores.
Selecting Cpos by cross-validation.
Selecting Cneg by cross-validation.
Found 0 test set positives with q<0.01 in initial
direction
---Training with Cpos selected by cross validation,
Cneg selected by cross validation,
initial_fdr=0.01, fdr=0.01
Found 0 test set PSMs with q<0.01.
No targets found with q<0.01
Resetting score vector, using default vector. Use
--override flag to prevent this.
Selected best-scoring PSM per scan+expMass
(target-decoy competition): 3650 target PSMs and
3526 decoy PSMs.
Tossing out "redundant" PSMs keeping only the best
scoring PSM for each unique peptide.
Calculating q values.
Final list yields 0 target peptides with q<0.01.
Calculating posterior error probabilities (PEPs).
INFO ms2rescore.core // Identified -28 (-100.00%) less
PSMs at 1% FDR after rescoring.
INFO ms2rescore.core // Writing output to
/xtandemserver/download/output2.ms2rescore.psms.tsv
...
2025-07-14 15:22:12 INFO ms2rescore.report.generate // Collecting files...
INFO ms2rescore.report.generate // ✅ Found PSMs:
'/xtandemserver/download/output2.ms2rescore.psms.ts
v'
INFO ms2rescore.report.generate // ✅ Found
configuration:
'/xtandemserver/download/output2.ms2rescore.full-co
nfig.json'
INFO ms2rescore.report.generate // ✅ Found feature
names:
'/xtandemserver/download/output2.ms2rescore.feature
_names.tsv'
WARNING ms2rescore.report.generate // ❌ feature weights:
'/xtandemserver/download/output2.ms2rescore.mokapot
.weights.tsv'
INFO ms2rescore.report.generate // ✅ Found log:
'/xtandemserver/download/output2.ms2rescore.log.txt
'
INFO ms2rescore.report.generate // Recalculating
confidence estimates...
INFO mokapot.dataset // Using 1 features:
INFO mokapot.dataset // (1) before
INFO mokapot.dataset // Found 7176 PSMs.
INFO mokapot.dataset // - 3650 target PSMs and 3526
decoy PSMs detected.
2025-07-14 15:22:13 INFO mokapot.dataset // Using 1 features:
INFO mokapot.dataset // (1) after
INFO mokapot.dataset // Found 7176 PSMs.
INFO mokapot.dataset // - 3650 target PSMs and 3526
decoy PSMs detected.
ERROR ms2rescore._main_ // single positional indexer is
out-of-bounds
╭─────── Traceback (most recent call last) ───────╮
│ /usr/local/lib/python3.10/dist-packages/ms2resc │
│ ore/_main_.py:178 in main │
│ │
│ 175 │ │
│ 176 │ # Run MS²Rescore │
│ 177 │ try: │
│ ❱ 178 │ │ rescore(configuration=config) │
│ 179 │ except Exception as e: │
│ 180 │ │ LOGGER.exception(e) │
│ 181 │ │ sys.exit(1) │
│ │
│ /usr/local/lib/python3.10/dist-packages/ms2resc │
│ ore/core.py:156 in rescore │
│ │
│ 153 │ # Write report │
│ 154 │ if config["write_report"]: │
│ 155 │ │ try: │
│ ❱ 156 │ │ │ generate.generate_report( │
│ 157 │ │ │ │ output_file_root, psm_lis │
│ use_txt_log=True │
│ 158 │ │ │ ) │
│ 159 │ │ except exceptions.ReportGeneratio │
│ │
│ /usr/local/lib/python3.10/dist-packages/ms2resc │
│ ore/report/generate.py:90 in generate_report │
│ │
│ 87 │ confidence_before, confidence_after = │
│ 88 │ │
│ 89 │ overview_context = _get_overview_cont │
│ ❱ 90 │ target_decoy_context = _get_target_de │
│ 91 │ features_context = _get_features_cont │
│ feature_names=feature_names) │
│ 92 │ config_context = _get_config_context( │
│ 93 │ log_context = _get_log_context(files) │
│ │
│ /usr/local/lib/python3.10/dist-packages/ms2resc │
│ ore/report/generate.py:238 in │
│ _get_target_decoy_context │
│ │
│ 235 │ │ │ { │
│ 236 │ │ │ │ "title": TEXTS["charts"][ │
│ 237 │ │ │ │ "description": TEXTS["cha │
│ ❱ 238 │ │ │ │ "chart": charts.score_his │
│ 239 │ │ │ }, │
│ 240 │ │ │ { │
│ 241 │ │ │ │ "title": TEXTS["charts"][ │
│ │
│ /usr/local/lib/python3.10/dist-packages/ms2resc │
│ ore/report/charts.py:85 in score_histogram │
│ │
│ 82 │ # Get score thresholds │
│ 83 │ if all(psm_df["qvalue"]): │
│ 84 │ │ score_threshold = ( │
│ ❱ 85 │ │ │ psm_df[psm_df["qvalue"] <= 0. │
│ 86 │ │ │ .sort_values("qvalue", ascend │
│ 87 │ │ │ .iloc[0] │
│ 88 │ │ ) │
│ │
│ /usr/local/lib/python3.10/dist-packages/pandas/ │
│ core/indexing.py:1073 in _getitem_ │
│ │
│ 1070 │ │ │ axis = self.axis or 0 │
│ 1071 │ │ │ │
│ 1072 │ │ │ maybe_callable = com.apply_i │
│ ❱ 1073 │ │ │ return self._getitem_axis(ma │
│ 1074 │ │
│ 1075 │ def _is_scalar_access(self, key: tup │
│ 1076 │ │ raise NotImplementedError() │
│ │
│ /usr/local/lib/python3.10/dist-packages/pandas/ │
│ core/indexing.py:1625 in _getitem_axis │
│ │
│ 1622 │ │ │ │ raise TypeError("Cannot │
│ 1623 │ │ │ │
│ 1624 │ │ │ # validate the location │
│ ❱ 1625 │ │ │ self._validate_integer(key, │
│ 1626 │ │ │ │
│ 1627 │ │ │ return self.obj._ixs(key, ax │
│ 1628 │
│ │
│ /usr/local/lib/python3.10/dist-packages/pandas/ │
│ core/indexing.py:1557 in _validate_integer │
│ │
│ 1554 │ │ """ │
│ 1555 │ │ len_axis = len(self.obj._get_axi │
│ 1556 │ │ if key >= len_axis or key < -len │
│ ❱ 1557 │ │ │ raise IndexError("single pos │
│ 1558 │ │
│ 1559 │ # ---------------------------------- │
│ 1560 │
╰─────────────────────────────────────────────────╯
IndexError: single positional indexer is
out-of-bounds
This happens during the call to score_histogram in report/charts.py. It seems like psm_df[psm_df["qvalue"] <= 0.01] might be empty, possibly because no target PSMs were identified at 1% FDR.