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OpenMS
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The feature detection application for quantitation (centroided).
| pot. predecessor tools | → FeatureFinderCentroided → | pot. successor tools |
|---|---|---|
| PeakPickerHiRes | FeatureLinkerUnlabeled (or another feature grouping tool) | |
| SeedListGenerator | MapAlignerPoseClustering (or another alignment tool) |
Reference:
Weisser et al.: An automated pipeline for high-throughput label-free quantitative proteomics (J. Proteome Res., 2013, PMID: 23391308).
This module identifies "features" in a LC/MS map. By feature, we understand a peptide in a MS sample that reveals a characteristic isotope distribution. The algorithm computes positions in rt and m/z dimension and a charge estimate of each peptide.
The algorithm identifies pronounced regions of the data around so-called seeds. In the next step, we iteratively fit a model of the isotope profile and the retention time to these data points. Data points with a low probability under this model are removed from the feature region. The intensity of the feature is then given by the sum of the data points included in its regions.
How to find suitable parameters and details of the different algorithms implemented are described in the "TOPP tutorial" (on https://openms.readthedocs.io/).
Specialized tools are available for some experimental techniques: IsobaricAnalyzer.
The command line parameters of this tool are:
stty: 'standard input': Inappropriate ioctl for device
FeatureFinderCentroided -- Detects two-dimensional features in LC-MS data.
Full documentation: http://www.openms.de/doxygen/nightly/html/TOPP_FeatureFinderCentroided.html
Version: 3.4.0-pre-nightly-2024-12-16 Dec 17 2024, 02:41:12, Revision: 96ad74c
To cite OpenMS:
+ Pfeuffer, J., Bielow, C., Wein, S. et al.. OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data. Nat Methods (2024). doi:10.1038/s41592-024-02197-7.
To cite FeatureFinderCentroided:
+ Sturm M. A novel feature detection algorithm for centroided data. Dissertation, 2010-09-15, p.37 ff. doi:https://publikationen.uni-tuebingen.de/xmlui/bitstream/handle/10900/49453/pdf/Dissertation_Marc_Sturm.pdf.
Usage:
FeatureFinderCentroided <options>
This tool has algorithm parameters that are not shown here! Please check the ini file for a detailed description or use the --helphelp option
Options (mandatory options marked with '*'):
-in <file>* Input file (valid formats: 'mzML')
-out <file>* Output file (valid formats: 'featureXML')
-seeds <file> User specified seed list (valid formats: 'featureXML')
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)
The following configuration subsections are valid:
- algorithm Algorithm section
You can write an example INI file using the '-write_ini' option.
Documentation of subsection parameters can be found in the doxygen documentation or the INIFileEditor.
For more information, please consult the online documentation for this tool:
- http://www.openms.de/doxygen/nightly/html/TOPP_FeatureFinderCentroided.html
INI file documentation of this tool:
For the parameters of the algorithm section see the algorithms documentation:
centroided
In the following table you can find example values of the most important parameters for different instrument types.
These parameters are not valid for all instruments of that type, but can be used as a starting point for finding suitable parameters.
'centroided' algorithm:
| Q-TOF | LTQ Orbitrap | |
| intensity:bins | 10 | 10 |
| mass_trace:mz_tolerance | 0.02 | 0.004 |
| isotopic_pattern:mz_tolerance | 0.04 | 0.005 |
For the centroided algorithm centroided data is needed. In order to create centroided data from profile data use the PeakPickerHiRes.
1.9.1