OpenMS  2.7.0

The feature detection application for quantitation.

pot. predecessor tools $ \longrightarrow $ FeatureFinderIsotopeWavelet $ \longrightarrow $ pot. successor tools
NoiseFilterSGolay MapAlignerPoseClustering
(or another alignment tool)
NoiseFilterGaussian FeatureLinkerUnlabeled
(or another feature grouping tool)

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.

that the wavelet transform is very slow on high-resolution spectra (i.e. FT, Orbitrap). We recommend to use a noise or intensity filter to remove spurious points first and to speed-up the feature detection process.

Specialized tools are available for some experimental techniques: IsobaricAnalyzer.

The command line parameters of this tool are:

FeatureFinderIsotopeWavelet -- Detects two-dimensional features in LC-MS data.
Full documentation:
Version: 2.7.0 Sep 13 2021, 20:58:47, Revision: 9110e58
To cite OpenMS:
  Rost HL, Sachsenberg T, Aiche S, Bielow C et al.. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Meth. 2016; 13, 9: 741-748. doi:10.1038/nmeth.3959.

  FeatureFinderIsotopeWavelet <options>

This tool has algorithm parameters that are not shown here! Please check the ini file for a detailed descript
ion or use the --helphelp option.

Options (mandatory options marked with '*'):
  -in <file>*        Input file (valid formats: 'mzML')
  -out <file>*       Output file (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:

INI file documentation of this tool:

required parameter
advanced parameter
+FeatureFinderIsotopeWaveletDetects two-dimensional features in LC-MS data.
version2.7.0 Version of the tool that generated this parameters file.
++1Instance '1' section for 'FeatureFinderIsotopeWavelet'
in input fileinput file*.mzML
out output fileoutput file*.featureXML
log Name of log file (created only when specified)
debug0 Sets the debug level
threads1 Sets the number of threads allowed to be used by the TOPP tool
no_progressfalse Disables progress logging to command linetrue,false
forcefalse Overrides tool-specific checkstrue,false
testfalse Enables the test mode (needed for internal use only)true,false
+++algorithmAlgorithm section
max_charge3 The maximal charge state to be considered.1:∞
intensity_threshold-1.0 The final threshold t' is build upon the formula: t' = av+t*sd, where t is the intensity_threshold, av the average intensity within the wavelet transformed signal and sd the standard deviation of the transform. If you set intensity_threshold=-1, t' will be zero.
As the 'optimal' value for this parameter is highly data dependent, we would recommend to start with -1, which will also extract features with very low signal-to-noise ratio. Subsequently, one might increase the threshold to find an optimized trade-off between false positives and true positives. Depending on the dynamic range of your spectra, suitable value ranges include: -1, [0:10], and if your data features even very high intensity values, t can also adopt values up to around 30. Please note that this parameter is not of an integer type, s.t. you can also use t:=0.1, e.g.
intensity_typeref Determines the intensity type returned for the identified features. 'ref' (default) returns the sum of the intensities of each isotopic peak within an isotope pattern. 'trans' refers to the intensity of the monoisotopic peak within the wavelet transform. 'corrected' refers also to the transformed intensity with an attempt to remove the effects of the convolution. While the latter ones might be preferable for qualitative analyses, 'ref' might be the best option to obtain quantitative results. Please note that intensity values might be spoiled (in particular for the option 'ref'), as soon as patterns overlap (see also the explanations given in the class documentation of FeatureFinderAlgorihtmIsotopeWavelet).ref,trans,corrected
check_ppmfalse Enables/disables a ppm test vs. the averagine model, i.e. potential peptide masses are checked for plausibility. In addition, a heuristic correcting potential mass shifts induced by the wavelet is applied.true,false
hr_datafalse Must be true in case of high-resolution data, i.e. for spectra featuring large m/z-gaps (present in FTICR and Orbitrap data, e.g.). Please check a single MS scan out of your recording, if you are unsure.true,false
rt_votes_cutoff5 Defines the minimum number of subsequent scans where a pattern must occur to be considered as a feature.0:∞
rt_interleave1 Defines the maximum number of scans (w.r.t. rt_votes_cutoff) where an expected pattern is missing. There is usually no reason to change the default value.0:∞

For the parameters of the algorithm section see the algorithms documentation: