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IDPosteriorErrorProbability

Tool to estimate the probability of peptide hits to be incorrectly assigned.

potential predecessor tools $ \longrightarrow $ IDPosteriorErrorProbability $ \longrightarrow $ potential successor tools
MascotAdapter (or other ID engines) ConsensusID
Experimental classes:
This tool has not been tested thoroughly and might behave not as expected!

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 incorreclty assigned sequences. At the moment, IDPosteriorErrorProbability is able to handle Xtandem, Mascot and OMSSA scores.

In order to validate the computed probabilities one can adjust the fit_algorithm subsection. The easiest way, is to create a default ini file with the parameter -write_ini file_name. Afterwards, it is suggested to open the created ini-file with INIFileEditor. 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_onls is set, target_decoy information are avaible and a False Discoveray 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:

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


OpenMS / TOPP release 1.9.0 Documentation generated on Sun Oct 27 2013 01:11:36 using doxygen 1.8.4