OpenMS
IDDecoyProbability

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/nightly/html/TOPP_IDDecoyProbability.html
Version: 3.2.0-pre-nightly-2024-07-19 Jul 20 2024, 02:06:43, Revision: f10e72e
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.

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/nightly/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.
version3.2.0-pre-nightly-2024-07-19 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