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OpenMS
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Detects features in MS1 data based on peptide identifications.
| pot. predecessor tools | → FeatureFinderIdentification → | pot. successor tools |
|---|---|---|
| PeakPickerHiRes (optional) | ProteinQuantifier | |
| IDFilter |
Reference:
Weisser & Choudhary: Targeted Feature Detection for Data-Dependent Shotgun Proteomics (J. Proteome Res., 2017, PMID: 28673088).
This tool detects quantitative features in MS1 data based on information from peptide identifications (derived from MS2 spectra). It uses algorithms for targeted data analysis from the OpenSWATH pipeline.
The aim is to detect features that enable the quantification of (ideally) all peptides in the identification input. This is based on the following principle: When a high-confidence identification (ID) of a peptide was made based on an MS2 spectrum from a certain (precursor) position in the LC-MS map, this indicates that the particular peptide is present at that position, so a feature for it should be detectable there.
Targeted data analysis on the MS1 level uses OpenSWATH algorithms and follows roughly the steps outlined below.
1. Assay generation
Feature detection is based on assays for identified peptides, each of which incorporates the retention time (RT), mass-to-charge ratio (m/z), and isotopic distribution (derived from the sequence) of a peptide. Peptides with different modifications are considered different peptides. One assay will be generated for every combination of (modified) peptide sequence, charge state, and RT region that has been identified. The RT regions arise by pooling all identifications of the same peptide, considering a window of size extract:rt_window around every RT location that gave rise to an ID, and then merging overlapping windows.
2. Ion chromatogram extraction
Ion chromatograms (XICs) are extracted from the LC-MS data (parameter in). One XIC per isotope in an assay is generated, with the corresponding m/z value and RT range (variable, depending on the RT region of the assay).
3. Feature detection
Next feature candidates - typically several per assay - are detected in the XICs and scored. A variety of scores for different quality aspects are calculated by OpenSWATH.
4. Feature classification
Feature candidates are classed as "negative" (candidates without matching IDs), "positive" (the single best candidate per assay with matching IDs), and "ambiguous" (other candidates with matching IDs).
5. Feature filtering
Feature candidates are filtered so that at most one feature per peptide and charge state remains; only candidates previously classed as "positive" are kept.
6. Elution model fitting
Elution models can be fitted to the features to improve the quantification. For robustness, one model is fitted to all isotopic mass traces of a feature in parallel. A symmetric (Gaussian) and an asymmetric (exponential-Gaussian hybrid) model type are available. The fitted models are checked for plausibility before they are accepted.
Finally the results (feature maps, parameter out) are returned.
Ion Mobility Support (experimental)
This tool supports two types of ion mobility data:
FAIMS (Field Asymmetric Ion Mobility Spectrometry): FAIMS data is automatically detected based on compensation voltage (CV) annotations in the mzML file. The data is split by CV and processed separately for each voltage group. Features representing the same analyte detected at different CV values are merged by default (controlled by faims:merge_features). No special preparation of the input mzML file is required.
Bruker TimsTOF (trapped ion mobility): The .d directory (or a zipped .d.zip) can be given as input directly: its MS1 data is read as one spectrum per frame, with the ion mobility of every peak. An mzML file with the same layout can be created with msconvert and its --combineIonMobilitySpectra option:
Ion mobility values from peptide identifications (if present in the idXML) are used for IM-aware feature detection. The extraction window is controlled by extract:IM_window.
The command line parameters of this tool are:
FeatureFinderIdentification -- Detects features in MS1 data based on peptide identifications.
Full documentation: http://www.openms.de/doxygen/nightly/html/TOPP_FeatureFinderIdentification.html
Version: 3.6.0-pre-nightly-2026-09-29 Sep 30 2026, 01:45:35, Revision: 55f7bdb
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.
To cite FeatureFinderIdentification:
+ Weisser H, Choudhary JS. Targeted Feature Detection for Data-Dependent Shotgun Proteomics. J. Proteome
Res. 2017; 16, 8:2964-2974. doi:10.1021/acs.jproteome.7b00248.
Usage:
FeatureFinderIdentification <options>
Options (mandatory options marked with '*'):
-in <file>* Input file: LC-MS raw data (valid formats: 'mzML', 'd', 'raw')
-id <file>* Input file: Peptide identifications derived directly from 'in' (valid
formats: 'idXML', 'idparquet')
-out <file>* Output file: Features (valid formats: 'featureXML', 'featureparquet')
-lib_out <file> Output file: Assay library (valid formats: 'traML')
-chrom_out <file> Output file: Chromatograms (valid formats: 'mzML')
-candidates_out <file> Output file: Feature candidates (before filtering and model fitting)
(valid formats: 'featureXML', 'featureparquet')
-quantify_decoys Whether decoy peptides should be quantified (true) or skipped (false).
-min_psm_cutoff <text> Minimum score for the best PSM of a spectrum to be used as seed. Use
'none' for no cutoff. (default: 'none')
-add_mass_offset_peptides <value> If for every peptide (or seed) also an offset peptide is extracted (tru
e). Can be used to downstream to determine MBR false transfer rates.
(0.0 = disabled) (default: '0.0') (min: '0.0')
Parameters for ion chromatogram extraction:
-extract:batch_size <number> Nr of peptides used in each batch of chromatogram extraction. Smaller
values decrease memory usage but increase runtime. (default: '5000')
(min: '1')
-extract:mz_window <value> M/z window size for chromatogram extraction (unit: ppm if 1 or greater,
else Da/Th) (default: '10.0') (min: '0.0')
-extract:IM_window <value> Ion mobility (IM) window for chromatogram extraction in the IM dimensio
n. Set to 0.0 to disable IM filtering (even if data contains IM informa
tion). The window is applied as +/- IM_window/2 around the median IM
value of identified peptides. This parameter is automatically ignored
if the input data does not contain IM information (determined via IMTyp
es::determineIMFormat). Currently only concatenated IM format is suppor
ted. Typical values: 0.05-0.10 for TIMS data (1/K0 units), 10-50 for
CCS data (square angstroms), 3-5 for FAIMS data (compensation voltage).
...
es (IM_median, IM_min, IM_max) for quality control. (default: '0.06')
(min: '0.0')
-extract:n_isotopes <number> Number of isotopes to include in each peptide assay. (default: '2')
(min: '2')
Parameters for detecting features in extracted ion chromatograms:
-detect:peak_width <value> Expected elution peak width in seconds, for smoothing (Gauss filter).
Also determines the RT extration window, unless set explicitly via 'ext
ract:rt_window'. (default: '60.0') (min: '0.0')
-detect:mapping_tolerance <value> RT tolerance (plus/minus) for mapping peptide IDs to features. Absolute
value in seconds if 1 or greater, else relative to the RT span of the
feature. (default: '0.0') (min: '0.0')
Parameters for fitting elution models to features:
-model:type <choice> Type of elution model to fit to features (default: 'symmetric') (valid:
'symmetric', 'asymmetric', 'none')
Parameters for fitting exp. mod. Gaussians to mass traces.:
-EMGScoring:max_iteration <number> Maximum number of iterations for EMG fitting. (default: '100') (min:
'1')
-EMGScoring:init_mom <choice> Alternative initial parameters for fitting through method of moments.
(default: 'true') (valid: 'true', 'false')
Parameters for FAIMS data processing:
-faims:merge_features <choice> For FAIMS data with multiple compensation voltages: Merge features that
represent the same analyte detected at different CVs. Features are
merged if they have the same charge and are within 5 seconds RT and
0.05 Da m/z. Intensities are summed. (default: 'true') (valid: 'true',
'false')
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 (0 =
all available cores) (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