Tool to estimate the probability of peptide hits to be incorrectly assigned.
potential predecessor tools | ![]() ![]() | 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 an optional plot output can be generated. There are two parameters for the plot: 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. The parameter 'out_plot' 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 PeptideIdentification are used for the estimation process. Additionally, if 'top_hits_only' is set and 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('out_plot' must not be empty). A peptide hit is assumed to be a target if its q-value is smaller than fdr_for_targets_smaller. The plots are saved as a gnuplot file. An attempt is made to call Gnuplot, which will create a PDF file which contains all steps of the estimation. If this fails, the user has to run Gnuplot manually or adjust the PATH environment such that this tool can find it.
The command line parameters of this tool are:
INI file documentation of this tool:
For the parameters of the algorithm section see the algorithms documentation:
fit_algorithm
OpenMS / TOPP release 2.0.0 | Documentation generated on Tue Nov 1 2016 16:34:46 using doxygen 1.8.11 |