Util to estimate probability of peptide hits

pot. predecessor tools	→ IDDecoyProbability →	pot. successor tools
MascotAdapter (or other ID engines)		-
PeptideIndexer		-

Experimental classes:: This util is deprecated and might behave not as expected!

So far an estimation of the false score distribution with a gamma distribution and the correct score distribution with a gaussian distribution is performed. The probabilities are calculated using Bayes law, similar to PeptideProphet. This implementation is much simpler than that of PeptideProphet.

Note: Currently mzIdentML (mzid) is not directly supported as an input/output format of this tool. Convert mzid files to/from idXML using IDFileConverter if necessary.

The command line parameters of this tool are:

IDDecoyProbability -- Estimates peptide probabilities using a decoy search strategy.
WARNING: This util is deprecated.
Full documentation: http://www.openms.de/doxygen/release/3.1.0/html/TOPP_IDDecoyProbability.html
Version: 3.1.0 Oct 18 2023, 10:27:18, Revision: 17a07f8
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:
  IDDecoyProbability <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>         Identification input of combined forward decoy search (reindex with PeptideIndexer first
                     ) (valid formats: 'idXML')
  -fwd_in <file>     Identification input of forward run (valid formats: 'idXML')
  -rev_in <file>     Identification input of decoy run (valid formats: 'idXML')
  -out <file>*       Identification output with forward scores converted to probabilities (valid formats: 
                     'idXML')
                     
                     
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:
 - decoy_algorithm   Algorithm parameter subsection

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/release/3.1.0/html/TOPP_IDDecoyProbability.html

INI file documentation of this tool:

Legend:

required parameter

advanced parameter

+IDDecoyProbabilityEstimates peptide probabilities using a decoy search strategy.
WARNING: This util is deprecated.

version3.1.0 Version of the tool that generated this parameters file.

++1Instance '1' section for 'IDDecoyProbability'

in Identification input of combined forward decoy search (reindex with PeptideIndexer first)input file*.idXML

fwd_in Identification input of forward runinput file*.idXML

rev_in Identification input of decoy runinput file*.idXML

out Identification output with forward scores converted to probabilitiesoutput file*.idXML

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

+++decoy_algorithmAlgorithm parameter subsection

number_of_bins40 Number of bins used for the fitting, if sparse datasets are used, this number should be smaller

lower_score_better_default_value_if_zero50.0 This value is used if e.g. a E-value score is 0 and cannot be transformed in a real number (log of E-value)

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