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OpenMS
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Resolves ambiguous annotations of features with peptide identifications.
| potential predecessor tools | → IDConflictResolver → | potential successor tools |
|---|---|---|
| IDMapper | TextExporter | |
| FeatureLinkerUnlabeled (or another feature grouping algorithm) | ProteinQuantifier |
The peptide identifications are filtered so that only one identification with a single hit (with the best score) is associated to each feature. (If two IDs have the same best score, either one of them may be selected.)
The the filtered identifications are added to the vector of unassigned peptides and also reduced to a single best hit.
When resolve_method is set to rank_aggregation, the tool aggregates peptide hit candidate lists across all identifications of a feature (i.e. across replicates) using rank-based scoring. Each unique sequence receives a rank in every identification in which it appears (rank 0 = best hit). Sequences absent from an identification receive a penalty rank equal to the maximum number of considered hits. The sequence with the best average rank score is selected as the winner.
This step may be useful before applying ProteinQuantifier, because features with ambiguous annotation are not considered for the quantification.
The command line parameters of this tool are:
IDConflictResolver -- Resolves ambiguous annotations of features with peptide identifications
Full documentation: http://www.openms.de/doxygen/nightly/html/TOPP_IDConflictResolver.html
Version: 3.6.0-pre-nightly-2026-03-23 Mar 24 2026, 01:47:13, Revision: c9a2677
To cite OpenMS:
+ Pfeuffer, J., Bielow, C., Wein, S. et al.. OpenMS 3 enables reproducible analysis of large-scale mass spec
trometry data. Nat Methods (2024). doi:10.1038/s41592-024-02197-7.
Usage:
IDConflictResolver <options>
Options (mandatory options marked with '*'):
-in <file>* Input file (data annotated with identifications) (val
id formats: 'featureXML', 'consensusXML')
-out <file>* Output file (data with one peptide identification
per feature) (valid formats: 'featureXML', 'consensus
XML')
-resolve_method <resolve_method> Method used to select the final peptide identificatio
n from (potentially multiple) identifications of a
feature.
'best_score': Keep the single best-scoring identifica
tion per feature (default).
'rank_aggregation': Aggregate all identifications of
a feature by rank across replicates. Each unique sequ
ence receives a rank in every identification in which
...
e with the best average rank score is selected. (defa
ult: 'best_score') (valid: 'best_score', 'rank_aggreg
ation')
-resolve_between_features <resolve_between_features> A map may contain multiple features with both identic
al (possibly modified i.e. not stripped) sequence
and charge state. The feature with the 'highest inten
sity' is very likely the most reliable one. When swit
ched on, the filter removes the sequence annotation
from the lower intensity features, thereby resolving
the multiplicity. Only the most reliable features
for each (possibly modified i.e. not stripped) sequen
ce maintain annotated with this peptide sequence.
(default: 'off') (valid: 'off', 'highest_intensity')
Common TOPP options:
-ini <file> Use the given TOPP INI file
-threads <n> Sets the number of threads allowed to be used by the
TOPP tool (default: '1')
-write_ini <file> Writes the default configuration file
--help Shows options
--helphelp Shows all options (including advanced)
INI file documentation of this tool:
This section lists all parameters supported by the tool. Parameters are organized into hierarchical subsections that group related settings together. Subsections may contain further subsections or individual parameters.
Each parameter entry contains the following information:
Parameter tags provide additional information about how a parameter is used. Some tags indicate whether a parameter is required or intended for advanced configuration, while others may be used internally by OpenMS or workflow tools.
Parameters highlighted as required must be specified for the tool to run successfully. Parameters marked as advanced allow fine-tuning of algorithm behavior and are typically not needed for standard workflows.
1.9.8