Groups corresponding features from multiple maps using a QT clustering approach.

potential predecessor tools	$\longrightarrow$ FeatureLinkerUnlabeledQT $\longrightarrow$	potential successor tools
FeatureFinderCentroided (or another feature detection algorithm)		ProteinQuantifier
MapAlignerPoseClustering (or another map alignment algorithm)		TextExporter
		SeedListGenerator

Reference:
Weisser et al.: An automated pipeline for high-throughput label-free quantitative proteomics (J. Proteome Res., 2013, PMID: 23391308).

This tool provides an algorithm for grouping corresponding features in multiple runs of label-free experiments. For more details and algorithm-specific parameters (set in the ini file) see "Detailed Description" in the algorithm documentation".

FeatureLinkerUnlabeledQT takes several feature maps (featureXML files) and stores the corresponding features in a consensus map (consensusXML file). Feature maps can be created from MS experiments (peak data) using one of the FeatureFinder TOPP tools.

See also: FeatureLinkerUnlabeled FeatureLinkerLabeled

The command line parameters of this tool are:

FeatureLinkerUnlabeledQT -- Groups corresponding features from multiple maps.
Version: 2.4.0 Oct 29 2018, 15:52:19, Revision: 9690d06
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.

Usage:
  FeatureLinkerUnlabeledQT <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 <files>*        Input files separated by blanks (valid formats: 'featureXML', 'consensusXML')
  -out <file>*        Output file (valid formats: 'consensusXML')
  -design <file>      Input file containing the experimental design (valid formats: 'tsv')
                      
  -keep_subelements   For consensusXML input only: If set, the sub-features of the inputs are transferred to 
                      the output.
                      
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 parameters 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.
Have a look at the OpenMS documentation for more information.

INI file documentation of this tool:

Legend:

required parameter

advanced parameter

+FeatureLinkerUnlabeledQTGroups corresponding features from multiple maps.

version2.4.0 Version of the tool that generated this parameters file.

++1Instance '1' section for 'FeatureLinkerUnlabeledQT'

in[] input files separated by blanksinput file*.featureXML,*.consensusXML

out Output fileoutput file*.consensusXML

design input file containing the experimental designinput file*.tsv

keep_subelementsfalse For consensusXML input only: If set, the sub-features of the inputs are transferred to the output.true,false

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 Overwrite tool specific checks.true,false

testfalse Enables the test mode (needed for internal use only)true,false

+++algorithmAlgorithm parameters section

use_identificationsfalse Never link features that are annotated with different peptides (only the best hit per peptide identification is taken into account).true,false

nr_partitions100 How many partitions in m/z space should be used for the algorithm (more partitions means faster runtime and more memory efficient execution )1:∞

ignore_chargefalse false [default]: pairing requires equal charge state (or at least one unknown charge '0'); true: Pairing irrespective of charge statetrue,false

ignore_adducttrue true [default]: pairing requires equal adducts (or at least one without adduct annotation); true: Pairing irrespective of adductstrue,false

++++distance_RTDistance component based on RT differences

max_difference100 Never pair features with a larger RT distance (in seconds).0:∞

exponent1 Normalized RT differences ([0-1], relative to 'max_difference') are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)0:∞

weight1 Final RT distances are weighted by this factor0:∞

++++distance_MZDistance component based on m/z differences

max_difference0.3 Never pair features with larger m/z distance (unit defined by 'unit')0:∞

unitDa Unit of the 'max_difference' parameterDa,ppm

exponent2 Normalized ([0-1], relative to 'max_difference') m/z differences are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)0:∞

weight1 Final m/z distances are weighted by this factor0:∞

++++distance_intensityDistance component based on differences in relative intensity (usually relative to highest peak in the whole data set)

exponent1 Differences in relative intensity ([0-1]) are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)0:∞

weight0 Final intensity distances are weighted by this factor0:∞

log_transformdisabled Log-transform intensities? If disabled, d = |int_f2 - int_f1| / int_max. If enabled, d = |log(int_f2 + 1) - log(int_f1 + 1)| / log(int_max + 1))enabled,disabled