Tool to estimate the probability of peptide hits to be incorrectly assigned.
| potential predecessor tools |  IDPosteriorErrorProbability   | potential successor tools | 
| MascotAdapter (or other ID engines) | ConsensusID | 
By default an estimation is performed using the (inverse) Gumbel distribution for incorrectly assigned sequences and a Gaussian distribution for correctly assigned sequences. The probabilities are calculated by using Bayes' law, similar to PeptideProphet. Alternatively, a second Gaussian distribution can be used for incorrectly assigned sequences. At the moment, IDPosteriorErrorProbability is able to handle X!Tandem, Mascot, MyriMatch and OMSSA scores.
No target/decoy information needs to be provided, since the model fits are done on the mixed distribution.
In order to validate the computed probabilities one can adjust the fit_algorithm subsection.
There are three parameters for the plot: The parameter 'output_plots' is by default false. If set to true the plot will be created. The scores are plotted in form of bins. Each bin represents a set of scores in a range of (highest_score - smallest_score)/number_of_bins (if all scores have positive values). The midpoint of the bin is the mean of the scores it represents. Finally, the parameter output_name should be used to give the plot a unique name. Two files are created. One with the binned scores and one with all steps of the estimation. If top_hits_only is set, only the top hits of each PeptideIndentification are used for the estimation process. Additionally, if 'top_hits_only' is set, target_decoy information are available and a False Discovery Rate run was performed before, an additional plot will be plotted with target and decoy bins(output_plot must be true in fit_algorithm subsection). A peptide hit is assumed to be a target if its q-value is smaller than fdr_for_targets_smaller.
Actually, the plots are saved as a gnuplot file. Therefore, to visualize the plots one has to use gnuplot, e.g. gnuplot file_name. This should output a postscript file which contains all steps of the estimation.
The command line parameters of this tool are:
IDPosteriorErrorProbability -- Estimates probabilities for incorrectly assigned peptide sequences and a set 
of search engine scores using a mixture model.
Version: 1.11.1 Nov 14 2013, 11:18:15, Revision: 11976
Usage:
  IDPosteriorErrorProbability <options>
This tool has algoritm parameters that are not shown here! Please check the ini file for a detailed descripti
on or use the --helphelp option.
Options (mandatory options marked with '*'):
  -in <file>*           Input file  (valid formats: 'idXML')
  -out <file>*          Output file  (valid formats: 'idXML')
  -output_name <file>*  Gnuplot file as txt (valid formats: 'txt')
  -split_charge         The search engine scores are split by charge if this flag is set. Thus, for each char
                        ge state a new model will be computed.
  -top_hits_only        If set only the top hits of every PeptideIdentification will be used
  -ignore_bad_data      If set errors will be written but ignored. Useful for pipelines with many datasets 
                        where only a few are bad, but the pipeline should run through.
  -prob_correct         If set scores will be calculated as 1-ErrorProbabilities and can be interpreted as 
                        probabilities for correct identifications.
                        
                        
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:
 - fit_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.
Have a look at the OpenMS documentation for more information.
INI file documentation of this tool:
For the parameters of the algorithm section see the algorithms documentation: 
 fit_algorithm 
| OpenMS / TOPP release 1.11.1 | Documentation generated on Thu Nov 14 2013 11:19:24 using doxygen 1.8.5 |